Nucleic acid biomarkers for prostate cancer

ABSTRACT

This invention relates to microRNA biomarkers useful in the diagnosis and prognosis of prostate cancer. The biomarkers are also useful for the monitoring and/or treatment of prostate cancer.

This application claims the benefit of UK applications GB 1218219.2(filed 10 Oct. 2012) and GB 1311958.1 (filed 3 Jul. 2013), the completecontents of which are hereby incorporated herein by reference for allpurposes.

TECHNICAL FIELD

This invention relates to microRNA biomarkers useful in the diagnosisand/or prognosis of prostate cancer. The biomarkers are also useful forthe monitoring and/or treatment of prostate cancer.

BACKGROUND

Prostate cancer (PC) is a disease of the prostate, a gland in the malereproductive system. In a subset of men, PC is aggressive and this formhas a high mortality. Currently, the severity of PC is measured on aclinically defined scale called the “Gleason scale” [1]. The Gleasonscale ranges between 1-5 (with “1” being defined as differentiatednormal healthy tissue and “5” being defined as undifferentiated,invasive tissue). Using this scale, pathologists interrogate themicroscopic appearance of PC histopathological slices and grade the mostcommon tumour pattern first, and then grade the next most common tumourpattern thereafter. These two grades are then combined to get a “Gleasonscore”. Areas of aggressive cancer in the prostate contain moreundifferentiated tissue, which are associated with a higher Gleasonscore and have a greater chance of metastases; the indolent form tendsto be slower growing, have a low Gleason score and therefore lessclinically significant. It has been clinically defined that aggressivePC must include one of the following criteria: a Gleason score of ≧7(4+3); a serum concentration of Prostate Specific Antigen (PSA;kallikrein 3) ≧20 ng/ml; regional- or distant-stage disease; and deathdue to metastatic PC [2,3]. Indolent PC, typically, is defined as havinga Gleason score of ≦7 (3+4); localised-stage disease; and death due tonon-PC related reasons. It is currently not possible to determine at anearly stage whether the cancer is indolent or aggressive, with the onlycurrent course of action being ‘watchful waiting’, also known as ‘activesurveillance’. Failure to diagnose and treat an aggressive form canresult in the metastasis of the cancer to surrounding tissues andassociated mortality; but over-treatment of patients with indolent PC isundesirable due to associated morbidity. Therefore, it is highlydesirable to identify the aggressive forms of PC early.

Although removal of prostatic tissue and pathological examination iscurrently the only accurate test for PC, it is preferable to minimisethe number of avoidable surgical procedures due to associated morbidity.Thus a biopsy is normally only recommended after receiving the resultsof an abnormal digital rectal examination (DRE) and evaluation of eitherthe serum concentration of PSA, or urine detection of Prostate CancerAntigen 3 (PCA3; DD3). PSA and PCA3 (both FDA approved) are currentlythe only two molecular markers approved for use in the context of PCdiagnosis with tens of millions of these tests being performed annually,worldwide. Reported specificities for the PSA test vary but in generalare much less than 50% [4]. A raised PSA level can indicate PC but it isalso seen in other conditions of the prostate such as benign prostatichypertrophy (BPH) and prostatitis. EU and US studies show that PSAshould not be used as a population screening tool, and currently thereis no biomarker approved for the prognosis of PC.

The poor performance of PSA has resulted in the search for alternativebiomarkers for the early diagnosis of PC e.g. the PCA3 or DD3 antigens[58], serum markers of reference 9, the gene expression profiles ofreference 10, the glycan profiles of reference 11, AMACR(alphamethylacyl CoA racemase), EPCA (early prostate carcinoma antigen),EPCA-2, gene promoter methylation, gene fusions including TMPRSS2:ERG,ERG/ETV1 gene rearrangements, PTEN gene loss, peptide fingerprints,metabolites including sarcosine, etc. A molecular test for PCA3 haseventually become the second FDA approved test for PC; although thereported specificity for this marker is higher than PSA (approximately70-80%), it has a much poorer sensitivity (approximately 60-70%) [3, 4,5] and the metrics obtained from a combination of the two tests (PSA andPCA3) is modest [12].

No current test can discriminate accurately between aggressive andindolent PC. Such a test would provide significant clinical benefit byenabling earlier active clinical management of aggressive cancers whilereducing unnecessary intervention for indolent cancers.

There is a need for new tests providing improved sensitivity andspecificity metrics to enable non-invasive diagnosis and/or prognosis ofPC. The discriminatory power of these diagnostic/prognostic tests shouldbe sufficiently high to support population-based screening approaches,something which PSA cannot achieve [13]. Ideally, they should be usefulfor the detection of PC at an early stage, and provide clinically usefulprognostic information. It is an objective of the invention to meetthese needs.

DISCLOSURE OF THE INVENTION

The invention is based on the identification of correlations between PCand the presence or absence of small non-coding miRNAs. The inventorshave identified miRNAs whose expression profiles can be used to indicatethat a subject has PC or to predict future disease progress. The miRNAscan also distinguish between aggressive PC and indolent PC. Detection ofthe presence or absence of these miRNAs, and/or of changes in theirlevels over time, can thus be used to indicate if a subject has PC, orhas the potential to develop aggressive PC. The miRNAs can therefore beconsidered as biomarkers of PC. Detection of these biomarkers in asubject sample can thus be used to improve the diagnosis, prognosis andmonitoring of PC. Advantageously, the invention can be used todistinguish between PC and other diseases of the prostate such as BPHand prostatitis where inflammation and raised PSA levels are common. Theinvention can also be used as a population screening tool, and can alsobe used alongside known tests for PC, such as PSA and/or PCA3 tests,pathological examination (e.g. Gleason score determination), etc.

The invention provides a method for analysing a subject sample,comprising a step of determining the level of a Table 17 biomarker inthe sample, wherein the level of the biomarker provides a diagnosticindicator of whether the subject has prostate cancer and/or a prognosticindicator of whether the subject has prostate cancer in the aggressiveform or indolent form.

The inventors have found that the miRNAs in Table 17 are particularlyuseful in detecting PC. A subset of the miRNAs in Table 17 is shown inTable 1, and the inventors found that these miRNAs are present atsignificantly different levels in subjects with PC and without PC. Thus,a miRNA in Table 1 is particularly useful in the method for providing adiagnostic indicator. Another subset of miRNAs in Table 17 is shown inTable 2, and the inventors found that these miRNAs are present atsignificantly different levels in subjects with aggressive PC andindolent PC. Thus, a miRNA in Table 2 is particularly useful in themethod as a prognostic indicator. As the miRNAs in Table 2 are alsopresent at significantly different levels in subjects with PC andwithout PC, a miRNA in Table 2 is also useful in the method forproviding a diagnostic indicator. Some markers are common to Tables 1and 2 and these are particularly useful in a joint diagnostic/prognosticmethod.

Analysis of a single Table 17 biomarker can be performed, and detectionof the miRNA can provide a useful diagnostic/prognostic indicator for PCeven without considering any of the other Table 17 biomarkers. Thesensitivity and specificity of diagnosis can be improved by combiningdata for multiple biomarkers. It is preferred to analyse more than oneTable 17 biomarker. Analysis of two or more different biomarkers (a“panel”) can enhance the sensitivity and/or specificity ofdiagnosis/prognosis compared to analysis of a single biomarker. Panelscan include marker(s) from Table 1 alone (e.g. a diagnostic panel), fromTable 2 alone (e.g. a prognostic panel), or from both of Tables 1 and 2(a joint diagnostic/prognostic panel).

Thus, the invention provides a method for analysing a subject sample,comprising a step of determining the levels of x different biomarkers ofTable 17, wherein the levels of the biomarkers provide a diagnosticindicator of whether the subject has PC and/or a prognostic indicator ofwhether the subject has PC of either the indolent or aggressive form.The value of x is 2 or more e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13,14, 15 or more (e.g. up to 35). These panels may include (i) anyspecific one of the 35 biomarkers in Table 17 in combination with (ii)any of the other 34 biomarkers in Table 17.

Suitable panels are described below for determining whether the subjecthas PC (Tables 3 to 9) and/or for determining PC prognosis (Tables 10 to16).

Where diagnosis is the primary interest, the invention provides a methodfor analysing a subject sample, comprising a step of determining thelevels of x different biomarkers of Table 1, wherein the levels of thebiomarkers provide a diagnostic indicator of whether the subject has PC.The value of x is 2 or more e.g. 2, 3, 4, 5, 6, 7, 8, 9, 10, or more(e.g. up to 21). These panels may include (i) any specific one of the 21biomarkers in Table 1 in combination with (ii) any of the other 20biomarkers in Table 1.

Where prognosis is the primary interest, the invention provides a methodfor analysing a subject sample, comprising a step of determining thelevels of x different biomarkers of Table 2, wherein the levels of thebiomarkers provide a prognostic indicator of whether the subject has PCof either the indolent or aggressive form. The value of x is 2 or moree.g. 2, 3, 4, 5, 6, 7, 8, 9, 10, or more (e.g. up to 17). These panelsmay include (i) any specific one of the 17 biomarkers in Table 2 incombination with (ii) any of the other 16 biomarkers in Table 2.

Preferred panels have from 1 to 7 biomarkers, as using more than 7biomarkers adds little to sensitivity and specificity.

The Table 17 biomarkers can be used in combination with one or more of:(a) known biomarkers for PC, which may or may not be miRNAs; and/or (b)other information about the subject from whom a sample was taken e.g.age, genotype, ethnicity, weight, other clinically-relevant data orphenotypic information; and/or (c) other diagnostic tests or clinicalindicators for PC, which can include, but are not limited to, Gleasonscore, PSA levels, tumour grading (TNM score), etc. Such combinationscan enhance the sensitivity and/or specificity of diagnosis and/orprognosis. Thus the invention provides a method for analysing a subjectsample, comprising a step of determining:

-   -   (a) the level(s) of y Table 17 biomarker(s), wherein the levels        of the biomarkers provide a diagnostic and/or prognostic        indicator respectively of whether the subject has PC and whether        the PC is of the indolent or aggressive form; and also one or        both of:    -   (b) if a sample from the subject contains a known biomarker        selected from the group consisting of PSA antigen, PCA3 antigen        and/or mRNA, DD3 antigen and/or mRNA, AMACR antigen and/or mRNA,        EPCA antigen and/or mRNA, EPCA-2 antigen and/or mRNA, gene        promoter methylation, TMPRSS2:ERG gene fusions, and sarcosine        (and optionally, any other known biomarkers e.g. see above);        wherein detection of the known biomarker provides a second        diagnostic and/or prognostic indicator of whether the subject        has PC;    -   (c) the subject's age,    -   and combining the different diagnostic and/or prognostic        indicators to provide an aggregate diagnostic and/or prognostic        indicator of whether the subject has PC and/or whether a PC is        of the indolent or aggressive form.

The samples used in (a) and (b) may be the same or different.

The value of y is 1 or more e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14, 15 (e.g. up to 35). When y>1 the invention uses a panel ofdifferent Table 17 biomarkers.

The invention also provides, in a method for diagnosing if a subject hasPC, an improvement consisting of determining in a sample from thesubject the level(s) of y biomarker(s) of Table 1, wherein the level(s)of the biomarker(s) provide a diagnostic indicator of whether thesubject has PC.

The invention also provides, in a method for predicting whether asubject has indolent or aggressive PC, an improvement consisting ofdetermining in a sample from the subject the level(s) of y biomarker(s)of Table 2, wherein the level(s) of the biomarker(s) provide aprognostic indicator of whether the subject has PC of either theindolent or aggressive form.

The invention also provides a method for diagnosing a subject as havingPC, comprising steps of: (i) determining the levels of y biomarkers ofTable 17 in a sample from the subject; and (ii) comparing thedetermination from step (i) to data obtained from samples from subjectswithout PC and/or from subjects with PC, wherein the comparison providesa diagnostic indicator of whether the subject has PC. The comparison instep (ii) can use a classifier algorithm as discussed in more detailbelow. Preferably, the biomarkers are selected from Table 1.

The invention also provides a method for monitoring development (andhence prognosis) of PC in a subject, comprising steps of: (i)determining the levels of z₁ biomarker(s) of Table 2 in a first samplefrom the subject taken at a first time; and (ii) determining the levelsof z₂ biomarker(s) of Table 2 in a second sample from the subject takenat a second time, wherein: (a) the second time is later than the firsttime; (b) one or more of the z₂ biomarker(s) were present in the firstsample; and (c) a change in the level(s) of the biomarker(s) in thesecond sample compared with the first sample indicates the state of thePC. The expression of the biomarker(s) in the second sample may be up-or down-regulated in comparison to the first sample, for example, asindicated in Table 2. The relative level(s) of the biomarker(s) indicatewhether the prostate cancer is either in remission or is progressing.The combination of several bi-directional miRNA biomarkers (i.e.including one or more biomarkers that are up-regulated in the secondsample relative to the first sample and one or more biomarkers that aredown-regulated in the second sample relative to the first sample) can beused for diagnosis and/or prognosis. Thus, the method monitors thebiomarker(s) over time, with changing levels indicating whether thedisease is getting better or worse.

The disease development can be either an improvement or a worsening, andthis method may be used in various ways e.g. to monitor the naturalprogress of a disease, or to monitor the efficacy of a therapy beingadministered to the subject. Thus, a subject may receive a therapeuticagent before the first time, at the first time, or between the firsttime and the second time.

The value of z₁ is 1 or more e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14, 15 (e.g. up to 17). The value of z₂ is 1 or more e.g. 1, 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 (e.g. up to 17). The values ofz₁ and z₂ may be the same or different. If they are different, it isusual that z₁>z₂ as the later analysis (z₂) can focus on biomarkerswhich were already detected in the earlier analysis; in otherembodiments, however, z₂ can be larger than z₁ e.g. if previous datahave indicated that an expanded panel should be used; in otherembodiments z₂=z₁ e.g. so that, for convenience, the same panel can beused for both analyses. When z₁>1 or z₂>1, the biomarkers are differentbiomarkers.

The invention also provides a method for monitoring development of PC ina subject, comprising steps of: (i) determining the level of at least w₁Table 2 biomarkers in a first sample taken at a first time from thesubject; and (ii) determining the level of at least w₂ Table 2biomarkers in a second sample taken at a second time from the subject,wherein: (a) the second time is later than the first time; (b) at leastone biomarker is common to both the w₁ and w₂ biomarkers; (c) the levelof at least one biomarker common to both the w₁ and w₂ biomarkers isdifferent in the first and second samples, thereby indicating that thePC is progressing or regressing. Thus the method monitors the range ofbiomarkers over time, with a broadening in the number of detectedbiomarkers indicating that the disease is getting worse. As mentionedabove, this method may be used to monitor disease development in variousways.

The value of w₁ is 1 or more e.g. 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,13, 14, 15 (e.g. up to 17). The value of w₂ is 2 or more e.g. 1, 2, 3,4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 (e.g. up to 17). The values ofw₁ and w₂ may be the same or different. If they are different, it isusual that w₂>w₁, as the later analysis should focus on a biomarkerpanel that is at least as wide as the number already detected in theearlier analysis. There will usually be an overlap between the w₁ and w₂biomarkers (including situations where they are the same, such that thesame biomarkers are measured at two time points) but it is also possiblefor w₁ and w₂ to have no biomarkers in common.

Where the methods involve a first time and a second time, these timesmay differ by at least 1 day, 1 week, 1 month or 1 year. Samples may betaken regularly. The methods may involve measuring biomarkers in morethan 2 samples taken at more than 2 time points i.e. there may be a 3rdsample, a 4th sample, a 5th sample, etc.

The invention also provides a device for the diagnosis and/or prognosisof PC, wherein the device permits determination of the level(s) of yTable 17 biomarkers. The value of y is defined above. In someembodiments, the diagnostic device permits determination of the level(s)of biomarker(s) listed in Table 1. In some embodiments, the diagnosticdevice permits determination of the level(s) of biomarker(s) listed inTable 2. In some embodiments, the diagnostic device permitsdetermination of the levels of at least one biomarker listed in Table 1and at least one biomarker listed in Table 2. The device may also permitdetermination of whether a sample contains one or more of the known PCbiomarkers mentioned above e.g. PSA and/or PCA3, and/or other knownbiomarkers listed above.

The invention also provides a kit comprising (i) a diagnostic and/orprognostic device of the invention and (ii) instructions for using thedevice to detect y of the Table 17 biomarkers. The value of y is definedabove. The kit is useful in the diagnosis and/or prognosis of PC.

The invention also provides a kit comprising reagents for measuring thelevels of x different Table 17 biomarkers. The kit may also includereagents for determining whether a sample contains one or more of theknown PC biomarkers mentioned above e.g. PSA and/or PCA3, and/or otherknown biomarkers listed above. The value of x is defined above. The kitis useful in the diagnosis and/or prognosis of PC.

The invention also provides a kit comprising components for preparing adiagnostic device of the invention. For instance, the kit may compriseindividual detection reagents for x different biomarkers, such that aselection of those x biomarkers can be prepared.

The invention also provides a product comprising (i) one or moredetection reagents which permit measurement of x different Table 17biomarkers, and (ii) a sample from a subject.

The invention also provides a software product comprising (i) code thataccesses data attributed to a sample, the data comprising measurement ofy Table 17 biomarkers, and (ii) code that executes an algorithm forassessing the data to represent a level of y of the biomarkers in thesample. The software product may also comprise (iii) code that executesan algorithm for assessing the result of step (ii) to provide adiagnostic and/or prognostic indicator of PC. As discussed below,suitable algorithms for use in part (iii) include support vector machinealgorithms, artificial neural networks, tree-based methods, geneticprogramming, etc. The algorithm can preferably classify the data of part(ii) to distinguish between PC subjects and non-PC subjects based onmeasured biomarker levels in samples taken from such subjects. Thealgorithm can also preferably classify the data of part (ii) todistinguish between PC subjects with the indolent and aggressive formsof the disease based on measured biomarker levels in samples taken fromsuch subjects. The invention also provides methods for training suchalgorithms.

The invention also provides a computer which is loaded with and/or isrunning a software product of the invention.

The invention also extends to methods for communicating the results of amethod of the invention. This method may involve communicating assayresults and/or diagnostic and/or prognostic results. Such communicationmay be to, for example, technicians, physicians or patients. In someembodiments, detection methods of the invention will be performed in onecountry and the results will be communicated to a recipient in adifferent country.

The invention also provides the use of a Table 1 biomarker as adiagnostic biomarker for PC.

The invention also provides the use of a Table 2 biomarker as aprognostic biomarker for PC.

The invention also provides the use of x different Table 17 biomarkersas biomarkers for PC diagnosis and/or prognosis. The value of x isdefined above. These may include panels as defined above.

The invention also provides the use as combined biomarkers for PC of (a)at least y Table 17 biomarker(s) and (b) PSA, PCA3, DD3, AMACR, EPCA,EPCA-2, gene promoter methylation, TMPRSS2:ERG gene fusions, EGR/ETV1gene rearrangements, PTEN gene loss, and/or sarcosine (and optionally,any other known biomarkers e.g. see above). The value of y is definedabove. When y>1 the invention uses a panel of biomarkers of theinvention.

Biomarkers of the Invention

In total, thirty-eight (38) individual human miRNAs have been identifiedand these can be used as either diagnostic and/or prognostic PCbiomarkers. Within the 38 miRNAs, 24 miRNAs are particularly useful fordistinguishing between samples from subjects with PC and from subjectwithout PC. Details of these 2124 miRNAs are given in Table 1. Otherpreferred miRNA marker subsets are listed in Tables 24 and 27.

Additionally, within the 35 miRNAs, 17 miRNAs are particularly usefulfor distinguishing between samples from subjects with aggressive PC andfrom subjects with indolent PC. Details of these 17 miRNAs are given inTable 2. Table 18 provides further details of the miRNA biomarkers, asprovided by miRBase database (version 16, released, August 2010), suchas the precursor hairpin pre-miRNA sequences and the genomic location ofthe miRNA gene. In some instances, multiple precursor pre-miRNAs (i.e.from different genomic locations) lead to the same mature miRNAsequence. Additionally, a single pre-miRNA precursor may lead to one ormore mature miRNA sequences, such as sequences excised from the 5′ and3′ arms of the hairpin, as indicated in Table 18. The methods of theinvention can involve detecting and determining the levels of the maturemiRNA sequences that are excised from 5′ and/or 3′ arms of the pre-miRNAprecursor, as indicated in Tables 1 and 2.

The specific sequences in Table 18 are not limiting on the invention.The invention includes detecting and measuring the levels of polymorphicvariants of these miRNAs. A database outlining in more detail the miRNAslisted herein is available: MiRBase [14, 15, 16, 17] or, in relation totarget prediction, the DIANA-microT [18, 19], microRNA.org [20], miRDB[21, 22], TargetScan [23] and PicTar [24] databases.

As mentioned above, detection of a single Table 1 biomarker can provideuseful diagnostic information, similarly detection of a single Table 2biomarker can provide useful prognostic information, but each biomarkermight not individually provide information which is useful i.e. a miRNAin Table 1 may be present in some, but not all, subjects with PC,additionally a miRNA in Table 2 may be present in some, but not all,subjects with aggressive PC. An inability of a single biomarker toprovide universal diagnostic and/or prognostic results for all subjectsdoes not mean that this biomarker has no diagnostic and/or prognosticutility, however, or else PSA also would not be useful; rather, any suchinability means that the test results (as in all diagnostic/prognostictests) have to be properly understood and interpreted.

To address the possibility that a single biomarker might not provideuniversal diagnostic and/or prognostic results, and to increase theoverall confidence that an assay is giving sensitive and specificresults across a disease population, it is advantageous to analyse aplurality of the Table 17 biomarkers (i.e. a panel). For instance, anegative signal for a particular Table 17 miRNA is not necessarilyindicative of the absence of PC, or indolent PC (just as a low PSAconcentration is not), but confidence that a subject does not have PC,or has indolent PC, increases as the number of negative resultsincreases. For example, in the diagnosis of PC if all 35 biomarkers aretested and are negative then the result provides a higher degree ofconfidence than if only 1 biomarker is tested and is negative.Similarly, in the prognosis of PC if all Table 2 biomarkers are testedand are negative then the result provides a higher degree of confidencethan if only 1 biomarker is tested and is negative that the subject hasindolent PC. Thus biomarker panels are most useful for enhancing thedistinction seen between diseased and non-diseased samples, as well asdetermining aggressive PC from indolent PC. As mentioned above,preferred panels have from 1 to 7 biomarkers as the burden of measuringa higher number of markers is usually not rewarded by better sensitivityor specificity. Preferred panels are given below.

Where a biomarker or panel provides a strong distinction between PC andnon-PC subjects, then a method for analysing a subject sample canfunction as a method for diagnosing if a subject has PC. Where abiomarker or panel provides a strong distinction between aggressive PCand indolent PC, then a method of analysing a subject sample canfunction as a method for prognosticating as to the aggressiveness of thePC. As with many diagnostic/prognostic tests, however, and as is alreadyknown for the PSA test, a method may not always provide a definitivediagnosis and/or prognosis and so a method for analysing a subjectsample can sometimes function only as a method for aiding in thediagnosis and/or prognosis of PC, or as a method for contributing to adiagnosis and/or prognosis of PC, where the method's result may implythat the subject has PC (e.g. the disease is more likely than not)and/or may confirm other diagnostic indicators (e.g. passed on clinicalsymptoms). Dealing with these considerations of certainty/uncertainty iswell known in the diagnostic/prognostic field.

Diagnosis and Prognosis

The invention involves diagnosis and/or prognosis of prostate cancer.

Diagnosis refers to the detection of the presence of PC in a subject.The biomarkers in Table 1 and Table 2 are present at significantlydifferent levels in subjects with PC compared to those without PC. Thus,these biomarkers are particularly useful as diagnostic indicators forPC.

Prognosis refers to predicting the likely outcome of the disease (i.e.PC) in a subject, including the likelihood that the PC patient willsuffer disease progression, including recurrence, metastatic spread, anddrug resistance, and a cancer-attributable death. The presence or levelof a biomarker of the invention may correlate with the risk orprogression of a disease or the susceptibility of the disease to certaintreatments. Thus, the detection and measurement of biomarkers of theinvention over time may provide a useful means to monitor the progressof disease, including recurrence or metastatic spread, such asindicating the stage of the PC.

The biomarkers in Table 2 are present at significantly different levelsin subjects with aggressive PC compared to those with indolent PC. Thus,the biomarkers in Table 2 are particularly useful as prognosticindicators. Hence, these biomarkers provide useful information for theaccurate prediction of outcomes in PC patients.

Clinical parameters that have been associated with a poor prognosis ofPC include advanced tumour stage, high PSA level at presentation, and aGleason score of over 7. However, the tumour staging and Gleason scorerely on identifying morphological changes of cells in tissue samples. Inparticular, it is difficult to morphologically differentiate betweenaggressive (which typically has a Gleason score of ≧7 (4+3)) andindolent PC (which typically has a Gleason score of ≦7 (3+4)). In someinstances, small focal aggressive cancer cells may go undetected at theearly stage. In contrast, the biomarkers of the invention areparticularly useful because the invention relies on detecting miRNAbiomarkers, which are molecular changes that precede cellular changes,so prognosis can be assessed at a much earlier stage. Hence, theinvention improves the prognostic accuracy of PC, thereby enabling theoptimal and early treatment and management of the patient.

The Subject

The invention is used for diagnosing disease in a subject, andprognosticating as to the aggressiveness of the disease. The subjectwill be male. The subject will usually be at least 20 years old(e.g. >25, >30, >35, >40, >45, >50, >55, >60, >65, >70). They willusually be at least 50 years old as the risk of PC increases in thesemen, and for these subjects it may be appropriate to offer a screeningservice for Table 17 biomarkers.

The subject may be pre-symptomatic for PC or may already be displayingclinical symptoms. For pre-symptomatic subjects the invention is usefulfor predicting that symptoms may develop in the future if nopreventative action is taken. For subjects already displaying clinicalsymptoms, the invention may be used to confirm or resolve anotherdiagnosis. For pre-symptomatic subjects and/or subjects alreadydisplaying clinical symptoms, the invention may be used to confirm theprognosis of the PC, i.e. whether the PC is indolent or aggressive. Thesubject may already have begun treatment for PC.

In some embodiments the subject may already be known to be predisposedto development of PC e.g. due to family or genetic links. In otherembodiments, the subject may have no such predisposition, and maydevelop the disease as a result of environmental factors e.g. as aresult of exposure to particular chemicals (such as toxins orpharmaceuticals), as a result of diet [25], as a result of infection,etc.

It is the intention that the invention can be implemented relativelyeasily and/or cheaply, it is the intention that the invention is notrestricted to being used in patients who are already suspected of havingPC. Rather, it can be used to screen the general population or a highrisk population e.g. men at least 20 years old, as listed above.

The subject will typically be a human being. In some embodiments,however, the invention is useful in non-human organisms e.g. mouse, rat,rabbit, guinea pig, cat, dog, horse, pig, cow, or non-human primate(monkeys or apes, such as macaques or chimpanzees). In non-humanembodiments, any method used for detection of miRNAs by the inventionwill typically be based on the relevant non-human ortholog of the humanmiRNA disclosed herein. In some embodiments animals can be usedexperimentally to monitor the impact of a therapeutic on a particularbiomarker.

The Sample

The invention analyses samples from subjects. Many types of sample caninclude miRNAs suitable for detection by the invention, but the samplewill typically be (homogenised) tissue and/or a body fluid. Suitablebody fluids include, but are not limited to, tissue, blood, serum,plasma, saliva, prostate tissue, prostate fluid (i.e. fluid whichimmediately surrounds the prostate in vivo), prostatic secretions,lymphatic fluid, a wound secretion, urine, faeces, mucus, sweat, tearsand/or cerebrospinal fluid. The sample is typically tissue, serum,plasma or urine.

Typically during a prostate biopsy, prostate tissue samples are obtainedfrom: (i) all major regions of the prostate so as to ensure complete“geographic” coverage, and/or (ii) any region of the prostate that maybe suspected to be cancerous, e.g. suspicious on transrectal ultrasoundor magnetic resonance imaging. A common method of prostate biopsy istransrectal ultrasound-guided prostate (TRUS) biopsy. For the miRNAs ofthe invention that demonstrate a field-effect, selecting sample regionsthat are suspected to be cancerous is not essential for detecting PC.

In some embodiments, a method of the invention involves an initial stepof obtaining the sample from the subject. In other embodiments, however,the sample is obtained separately from and prior to performing a methodof the invention. After a sample has been obtained then methods of theinvention could be performed in vitro. In other embodiments, however, amethod of the invention involves detecting the presence and/or absenceof the miRNA in vivo, for example, but not limited to, use of adetection probe (e.g. a radioactive probe) as a tracer for molecularimaging. Detection of biomarkers may be performed directly on a sampletaken from a subject, or the sample may be treated between being takenfrom a subject and being analysed. For example, a blood sample may betreated to remove cells, leaving plasma containing free-circulatingmiRNA for analysis, or to remove cells and various clotting factors,leaving serum containing free-circulating miRNA for analysis. Faecessamples usually require physical treatment prior to miRNA detection e.g.suspension, homogenisation and centrifugation. For some body fluids,though, such separation treatments are not usually required (e.g. urine,tears or saliva) but other treatments may be used. For example, varioustypes of sample may be subjected to treatments such as dilution,aliquoting, sub-sampling, heating, freezing, irradiation, etc. betweenbeing taken from the body and being analysed e.g. serum is usuallystored, frozen prior to analysis. Also, addition of processing reagentsis typical for various sample types e.g. addition of anticoagulants toblood samples.

A tissue sample can be preserved with a fixative (e.g. formalin) beforeit is analysed. A preserved sample can also be embedded (e.g.formalin-fixed, paraffin-embedded (FFPE) samples). Alternatively, afresh tissue sample can be used, and this sample is fresh frozen,without fixatives.

Expression differences of any given miRNA may vary depending on thecompartment being analysed (e.g. tissue vs plasma and/or serum).Typically, expression levels of a miRNA will be higher in tissue due tomore cells being present in any given sample; the cells will be rich inmiRNA. However, in plasma and/or serum, the miRNAs are free-circulating(due to release from the cells) and thus their concentration is greatlydiluted in the surrounding (liquid) environment. However, a lowerexpression level in, for example, plasma doesn't mean that the miRNA isless biologically relevant. Also, any contrary expression differencesmay be due, in part, to miRNAs being sequestered in the cells and notreleased into the surrounding blood.

Preferably, the invention uses a combination of different types ofsample, e.g. a prostate tissue sample and a blood sample. Thus, theinvention provides a method for analysing a subject's samples,comprising: (i) determining the expression level of a biomarker of theinvention in a prostate tissue sample; (ii) determining the expressionlevel of the biomarker in a bodily fluid sample; (iii) comparing thedeterminations from (i) and (ii), wherein the difference between (i) and(ii) indicates that the subject has PC and/or aggressive or indolent PC.The tissue sample can be a fresh tissue sample or a preserved tissuesample. The body fluid sample can be a blood sample.

A biomarker of the invention may have different absolute expressionlevels in different types of sample. Thus, when the expression levels ofthe same biomarker in different sample types are compared against acontrol, different relative expression profiles may be observed.

For example, a biomarker of the invention can have opposite relativeexpression profiles (i.e. up-regulation as opposed to down-regulation ina PC sample compared to a control) in different sample types of the samesubject. For example, a biomarker (e.g. hsa-miR-449a) can beup-regulated (e.g. PC sample vs. a control) in one sample type, e.g.prostate tissue samples, but down-regulated in another sample type, e.g.bodily fluid (e.g. blood) samples, from the same subject. This divergentbehaviour can enhance diagnosis or prediction of PC when both types ofsample are assessed.

A biomarker of the invention can have the same relative differentialexpression profile (e.g. up-regulation when comparing PC vs. a control)in various sample types. For example, a biomarker of the invention (e.g.hsa-miR-183*) can be up-regulated (when comparing PC vs. a control) indifferent sample types, e.g. tissue and bodily fluid (e.g. blood)samples.

The inventors have found that some biomarkers of the invention show a‘field-effect’ within the prostate gland, whereby differential relativeexpression profiles (e.g. PC sample compared to a control) can beobserved in samples from any part of the prostate. Hence, thesebiomarkers are able to detect or predict PC from a more generalised,less targeted, sampling of the prostate during a routine biopsyprocedure.

For example, the inventors found that hsa-miR-3621, hsa-miR-33b*,hsa-miR-1973, hsa-miR-375, hsa-miR-182, hsa-miR-183, hsa-miR-602,hsa-miR-1291, hsa-miR-103, hsa-miR-148*, hsa-miR-182*, hsa-miR-185,hsa-miR-191, hsa-miR-210 and hsa-miR-494, hsa-miR-582 have significantrelative differential expression profiles when samples from a non-PCregion of a diseased prostate are compared to a suitable control sample,which does not have of clinical presentation of PC, but, additionally,these markers have non-differential expression profiles when comparingsamples from different prostate regions in the same PC subject.

Thus, for miRNAs that demonstrate a field-effect, a method of theinvention can include determining the expression level of a biomarker ofthe invention in a tissue sample from any region of the prostate,wherein the expression level of the biomarker indicates that the subjecthas PC and/or aggressive or indolent PC. The method can further comprisedetermining the expression level of the biomarker in a control, andcomparing the expression levels of the biomarker in the tissue sampleand in the control, wherein a difference in the expression levelsindicate that the subject has PC and/or aggressive or indolent PC. Thesample can be from a region suspected to be cancerous in the prostate ora region in the prostate that has not been suspected to be cancerous.

Biomarker Detection

Table 17 lists 38 human miRNA molecules, and methods of the inventioncan involve detecting and determining the level of these miRNAbiomarker(s) in a sample. Table 18 also includes nucleotide sequencesfor these miRNA molecules, but polymorphisms of miRNA are known in theart and so the invention can also involve detecting and determining thelevel of a polymorphic miRNA variant of these listed miRNA sequences.

Techniques for detecting specific miRNAs are well known in the art, e.g.microarray analysis and NanoString's nCounter technology, polymerasechain reaction (PCR)-based methods (e.g. reverse transcription PCR,RT-PCR), in-situ hybridisation (ISH)-based methods (e.g. fluorescentISH, FISH), northern blotting, sequencing (e.g. next-generationsequencing), fluorescence-based detection methods, etc. Any of thedetection techniques mentioned above can be used with the invention.Where prognosis is the primary interest, a quantitative detectiontechnique is preferred, e.g. real-time quantitative PCR (qPCR), TaqMan®or SYBR® Green.

Detection of a miRNA typically involves contacting (“hybridising”) asample with a complementary detection probe (e.g. a syntheticoligonucleotide strand), wherein a specific (rather than non-specific)binding reaction between the sample and the complementary probeindicates the presence of the miRNA of interest. In some instances, themiRNA in the sample is amplified prior to detection, e.g. by reversetranscription of the miRNA to produce a complementary DNA (cDNA) strand,and the derived cDNA can be used as a template in the subsequent PCRreaction.

Thus, the invention provides nucleic acids, which can be used, forexample, as hybridization probes for specific detection of miRNA inbiological samples or as single-stranded primers to amplify the miRNA.

The term “nucleic acid” in general means a polymeric form of nucleotidesof any length, which contain deoxyribonucleotides, ribonucleotides,and/or their analogs. It includes DNA, RNA, DNA/RNA hybrids. It alsoincludes DNA or RNA analogs, such as those containing modified backbones(e.g. peptide nucleic acids (PNAs) or phosphorothioates) or modifiedbases. Nucleic acid according to the invention can take various forms(e.g. single-stranded, primers, probes, labelled etc.). Primers andprobes are generally single-stranded.

The nucleic acid can be identical or complementary to the mature miRNAsequences listed in Table 18, i.e. any one of SEQ ID NOs: 1-49. Thenucleic acid may comprise sequences found in the miRBase database.

The nucleic acid can comprise a nucleotide sequence that has ≧50%, ≧60%,≧70%, ≧75%, ≧80%, ≧85%, ≧90%, ≧95%, ≧96%, ≧97%, ≧98%, ≧99% or moreidentity to any one of SEQ ID NOs: 1-49. Identity between sequences ispreferably determined by the Smith-Waterman homology search algorithm asdescribed above.

The nucleic acid can comprise a nucleotide sequence that has ≧50%, ≧60%,≧70%, ≧75%, ≧80%, ≧85%, ≧90%, ≧95%, ≧96%, ≧97%, ≧98%, ≧99% or morecomplementarity to any one of SEQ ID NOs: 1-49. The term“complementarity” when used in relation to nucleic acids refers toWatson-Crick base pairing. Thus the complement of C is G, the complementof G is C, the complement of A is T (or U), and the complement of T (orU) is A. It is also possible to use bases such as I (the purine inosine)e.g. to complement pyrimidines (C or T).

Where a nucleic acid is DNA, it will be appreciated that “U” in a RNAsequence will be replaced by “T” in the DNA. Similarly, where a nucleicacid is RNA, it will be appreciated that “T” in a DNA sequence will bereplaced by “U” in the RNA.

The nucleic acid may be 12 or more, e.g. 12, 13, 14, 15, 16, 17 or 18,etc. (e.g. up to 50) nucleotides in length. The nucleic acid may be15-30 nucleotides in length, 10-25 nucleotides in length, 15-25nucleotides in length, or 20-25 nucleotides in length.

The nucleic acid may include sequences that do not hybridise to themiRNA biomarkers, and/or amplified products thereof. For example, thenucleic acid may contain additional sequences at the 5′ end or at the 3′end. The additional sequences can be a linker, e.g. for cloning or PCRpurposes.

Nucleic acid of the invention may be attached to a solid support (e.g. abead, plate, filter, film, slide, microarray support, resin, etc.).Nucleic acid of the invention may be labelled e.g. with a radioactive orfluorescent label, or a biotin label. This is particularly useful wherethe nucleic acid is to be used in detection techniques e.g. where thenucleic acid is a primer or as a probe. Methods for preparingfluorescent labelled probes, e.g. for fluorescent in-situ hybridisationFISH analysis, are known in the art, and FISH probes can be obtainedcommercially, e.g. from Exiqon.

The invention may use in-situ hybridisation (ISH)-based methods, e.g.fluorescent in-situ hybridisation (FISH). Hybridization reactions can beperformed under conditions of different “stringency” followed bywashing. Preferably, the nucleic acid of the invention hybridise underhigh stringency conditions, such that the nucleic acid specificallyhybridises to a miRNA in an amount that is detectably stronger thannon-specific hybridisation. Relatively high stringency conditionsinclude, for example, low salt and/or high temperature conditions, suchas provided by about 0.02-0.1 M NaCl or the equivalent, at temperaturesof about 50-70° C. A stringent wash removes non-specific probe bindingand overloaded probes. Relatively stringent wash conditions include, forexample, low salt and/or presence of detergent, e.g. 0.02% SDS in 1×Saline-Sodium Citrate (SSC) at about 50° C.

In embodiments where multiple biomarkers are to be detected, anarray-based assay or PCR format is preferable, in which a sample thatpotentially contains the biomarkers are simultaneously contacted withmultiple oligonucleotide complementary detection probes, or PCRprimers/probes (“multiplexed”) in a single reaction compartment, wherebya reaction compartment is defined as, but not limited to, a microtitrewell, microfluidic chamber or detection pore. In other embodiments thesemultiple biomarkers could either be contacted with its complementarydetection probe in separate, individual reaction compartments and/or;experiments could be separated over time and using different platformtechnologies in either multiplexed single reaction compartments orseparate, individual reaction compartments. Microarray and PCR usage forthe detection of miRNAs is well known in the art e.g. see reference 26and reference 27. Microarrays may be prepared by various techniques,such as those disclosed in references 28, 29, & 30. Methods based onnucleic acid amplification are also well known in the art.

Methods and apparatus for detecting binding reactions on DNA microarraysare now standard in the art. Preferred detection methods arefluorescence-based detection methods. To detect biomarkers which havebound to immobilised oligonucleotide strands on a glass substrate istypical e.g. in which the target miRNA is fluorescently labelled andthen is hybridised to a complementary oligonucleotide strand (probe).

An array is advantageous because it allows simultaneous detection ofmultiple biomarkers in a sample. Such simultaneous detection is notmandatory, however, and a panel of biomarkers can also be evaluated inseries. Thus, for instance, a sample could be split into sub-samples andthe sub-samples could be assayed in series. In this embodiment it maynot be necessary to complete analysis of the whole panel e.g. thediagnostic indicators obtained on a subset of the panel may indicatethat a patient has PC without requiring analysis of any further membersof the panel. Such incomplete analysis of the panel is encompassed bythe invention because of the intention or potential of the method toanalyse the complete panel.

As mentioned above, some embodiments of the invention can include acontribution from known tests for PC, such as PSA and/or PCA3 tests. Anyknown tests can be used e.g. total PSA score, PSA velocity, thePROGENSA™ assay for urinary PCA3 mRNA, etc. Typically, PSA levels lessthan 4 ng/ml in blood are considered as normal, 4-10 ng/ml may warrantfurther investigation, and >10 ng/ml is high.

DATA Interpretation

The invention involves a step of determining the level of Table 17biomarker(s). In some embodiments of the invention this determinationfor a particular marker can be a simple yes/no determination(qualitative), whereas other embodiments may require a quantitative orsemi-quantitative determination, still other embodiments may involve arelative determination (e.g. a ratio relative to another marker, or ameasurement relative to the same marker in a control sample), and otherembodiments may involve a threshold determination (e.g. a yes/nodetermination whether a level is above or below a threshold). A skilledperson can easily determine the relative change (e.g. up-regulation ordown-regulation) for any given miRNA marker relative to any particularcontrol of interest (e.g. a negative control or a positive control) inany given sample (e.g. a prostate sample or a blood sample).

For example, the absolute levels of a biomarker in a particular control(e.g. a non-PC subject who has BPH) may be different from that inanother control (e.g. a non-PC subject who has bladder cancer). It willbe appreciated the relative differential expression profiles (e.g. up-or down-regulation or fold-changes) observed for the biomarkers of theinvention (e.g. as provided in Tables 1, 2, 20, and 21 and FIGS. 2-11)might be applicable only for the specific control used in that study.

Usually biomarkers will be measured to provide quantitative orsemi-quantitative results (whether as relative concentration, absoluteconcentration, fold-change, etc.) as this gives more data for use withclassifier algorithms.

Usually the raw data obtained from an assay for determining thepresence, absence, or level (absolute or relative) require some sort ofmanipulation prior to their use. For instance, the nature of mostdetection techniques means that some signal will sometimes be seen evenif no miRNA is actually present and so this noise may be removed beforethe results are interpreted. Similarly, there may be a background levelof the miRNA in the general population which needs to be compensatedfor. Data may need scaling or standardising to facilitateinter-experiments comparisons. These and similar issues, and techniquesfor dealing with them, are well known in the art.

Various techniques are available to compensate for background signal ina particular experiment. For example, replicate measurements willusually be performed (e.g. using multiple features of the same detectionprobe on a single array) to determine intra-assay variation and averagevalues from the replicates can be compared (e.g. the median value ofbinding to replicate array features). Furthermore, standard markers canbe used to determine inter-assay variation and to permit calibrationand/or normalisation e.g. an array can include one or more standards forindicating whether measured signals should be proportionally increasedor decreased.

For example, an assay might include a step of analysing the level of oneor more control marker(s) in a sample e.g. levels of a miRNA unrelatedto PC. Signal may be adjusted according to distribution in a singleexperiment. For instance, signals in a single array experiment may beexpressed as a percentage of interquartile differences e.g. as [observedsignal−25th percentile]/[75th percentile−25th percentile]. Thispercentage may then be normalised e.g. using a standard quantilenormalisation matrix, such as disclosed in reference 31, in which allpercentage values on a single array are ranked and replaced by theaverage of percentages for miRNAs with the same rank on all arrays.Overall, this process gives data distributions with identical median andquartile values. Data transformations of this type are standard in theart for permitting valid inter-array comparisons despite variationbetween different experiments.

The level of a biomarker relative to a single baseline level may bedefined as a fold difference. Normally it is desirable to use techniquesthat can indicate a change of at least 1.5-fold e.g. ≧1.75-fold,≧2-fold, ≧2.5-fold, ≧5-fold, etc.

As well as compensating for variation which is inherent betweendifferent experiments, it can also be important to compensate forbackground levels of a biomarker which are present in the generalpopulation. Again, suitable techniques are well known. For example,levels of a particular miRNA in a sample will usually be measuredquantitatively or semi-quantitatively to permit comparison to thebackground level of that biomarker. Various controls can be used toprovide a suitable baseline for comparison, and choosing suitablecontrols is routine in the diagnostic field. Further details of suitablecontrols are given below.

The measured level(s) of Table 17 biomarker(s), after anycompensation/normalisation/etc., can be transformed into a diagnosticand/or prognostic result respectively in various ways. Thistransformation may involve an algorithm which provides a diagnosticand/or prognostic result as a function of the measured level(s). Where apanel is used then each individual biomarker may make a differentcontribution to the overall diagnostic and/or prognostic result and sotwo biomarkers may be weighted differently.

The creation of algorithms for converting measured levels or raw datainto scores or results is well known in the art. For example, linear ornon-linear classifier algorithms can be used. These algorithms can betrained using data from any particular technique for measuring themarker(s). Suitable training data will have been obtained by measuringthe biomarkers in “case” and “control” samples i.e. samples fromsubjects known to suffer from PC and from subjects known not to sufferfrom PC, also samples from subjects known to suffer from aggressive PCand from subjects known to suffer from indolent PC. Most usefully thecontrol samples will also include samples from subjects with a relateddisease which is to be distinguished from the disease of interest e.g.it is useful to train the algorithm with data from subjects withindolent PC and/or BPH subjects and/or with data from subjects withcancer(s) other than PC. The classifier algorithm is modified until itcan distinguish between the case and control samples e.g. by adding orremoving markers from the analysis, by changes in weighting, etc. Thus amethod of the invention may include a step of analysing biomarker levelsin a subject's sample by using a classifier algorithm whichdistinguishes between PC subjects and non-PC subjects based on measuredbiomarker levels in samples taken from such subjects.

Various suitable classifier algorithms are available e.g. lineardiscriminant analysis, naïve Bayes classifiers, regression modelling,perceptrons, support vector machines (SVM) [32] and genetic programming(GP) [33], as well as a series of statistical methods including, but notlimited to, Principal Component Analysis (PCA), unsupervisedhierarchical clustering and linear modelling. GP is particularly usefulas it generally selects relatively small numbers of biomarkers andovercomes the problem of trapping in a local maximum which is inherentin many other classification methods. SVM-based approaches havepreviously been used for PC diagnosis by classifying images of prostatetissue [34,35], patient data [36], or gene expression levels [10].Moreover, these approaches can potentially distinguish PC subjects fromsubjects with (i) indolent PC cancer (ii) other forms of cancer and(iii) confounding diseases such as BPH and prostatitis. The biomarkersin Table 17 can be used to train such algorithms to reliably make suchdistinctions. The average intensities of all oligonucleotide features oneach array will be normalised to reduce technical bias (e.g. laser powervariation, surface variation, input miRNA concentration, etc.) by apercentile normalisation procedure. Other methods for data normalisationsuitable for the data include, amongst others, quantile normalisation[41]. Such normalisation methods are known in the art of microarrayanalysis. The resulting data will be analysed for any potentialsignatures relating to differences between patient cohorts referring tolevels of statistical significance (generally p<0.05), multiple testingcorrection and fold changes within the expression data that could beindicative of biological effect (normally it is desirable to usetechniques that can indicate a change of at least 1.5 fold e.g. >1.75fold, >2-fold, >2.5-fold, >5-fold, etc.). The classification performance(sensitivity and specificity (S+S), Receiver Operator Curve (ROC)analysis) of any putative biomarkers will be rigorously assessed usingnested cross validation and permutation analyses prior to furthervalidation. Biological support for putative biomarkers will be soughtusing tools and databases including GeneSpring® (version 11.5.1), BioPAXpathway for GSEA analysis and Pathway Studio® (version 9.1).

It will be appreciated that, although there may be some biomarkers inTable 17 which always give a negative absolute signal when contactedwith negative control samples (and thus any positive signal isimmediately indicative of PC or aggressive PC, where applicable), it ismore common that a biomarker will give at least a low absolute signal(and thus that a disease-indicating positive signal requires detectionof miRNA levels above that background level). Thus references hereindetecting a biomarker may not be references to absolute detection butrather (as is standard in the art) to a level above the levels seen inan appropriate negative control. Such controls may be assayed inparallel to a test sample but it can be more convenient to use anabsolute control level based on empirical data, or to analyse data usingan algorithm which can (e.g. by previous training) use biomarker levelsto distinguish samples from disease patients vs. non-disease patients.

The level of a particular biomarker in a sample from a PC-diseasedsubject may be above or below the level seen in a negative controlsample (i.e. from a healthy subject). The expression of miRNAs caneither be up-regulated or down-regulated depending on the state of theindividual. In a control population of healthy individuals there maythus be significant levels of miRNAs disclosed in Table 17 and these mayoccur at a significant frequency in the population. The level andfrequency of these biomarkers may be altered in a disease cohort,compared with the control cohort. An analysis of the level and frequencyof these biomarkers in the case and control populations may identifydifferences which provide diagnostic information. The level of a miRNAbiomarker may increase or decrease in a PC sample, compared with ahealthy sample.

The inventors found that hsa-miR-205 and hsa-miR-221 have significantlyreduced levels in PC subjects compared to a sample taken from a non-PCregion from the same diseased prostate, from the same subject (see Table1). Thus, the detection of a reduced expression of one or more of thesebiomarkers in a subject relative to a negative control (e.g. a non-PCsubject) may indicate that the subject has PC. Preferably, the sample isa fresh tissue sample.

The inventors found that hsa-miR-3621, hsa-miR-33b* and hsa-miR-1973have significantly reduced levels in PC subjects compared to subjectswho do not have PC, but have bladder cancer. Thus, the detection of areduced expression of one or more of these biomarkers in a subjectrelative to a suitable control may indicate that the subject has PC.Preferably, the control is a sample from a subject who does not have PC,but may have a different disease e.g. bladder cancer. Preferably, thesample is a preserved prostate tissue sample (e.g. FFPE tissue sample).

The inventors found that hsa-miR-665, hsa-miR-582, hsa-miR-182,hsa-miR-378a, hsa-miR-96, hsa-miR-200b, hsa-miR-191, hsa-miR-429,hsa-miR-494, hsa-miR-99b*, hsa-miR-375, hsa-miR-141, hsa-miR-148*,hsa-miR-1291, hsa-miR-1973, hsa-miR-103, hsa-miR-3607-5p, hsa-miR-133band hsa-miR-210 have significantly reduced levels in PC subjectscompared to subjects who do not have PC, but have BPH. Thus, thedetection of a reduced expression of one or more of these biomarkers ina subject relative to a suitable control may indicate that the subjecthas PC. Preferably, the control is a sample from a subject who does nothave PC, but may have a different disease e.g. BPH. Preferably, thesample is a bodily fluid sample (e.g. a blood sample).

The inventors found that hsa-miR-665, hsa-miR-3621, hsa-miR-1973,hsa-miR-1291 and hsa-miR-183 have significantly reduced levels in PCsubjects compared to subjects who do not have PC, but have BPH. Thus,the detection of a reduced expression of one or more of these biomarkersin a subject relative to a suitable control may indicate that thesubject has PC. Preferably, the control is a sample from a subject whodoes not have PC, but may have a different disease e.g. BPH. Preferably,the sample is a bodily fluid sample (e.g. a blood sample). Preferably,the biomarker is any one of the group consisting of: hsa-miR-665,hsa-miR-3621, hsa-miR-1973 and hsa-miR-1291.

The inventors also found that hsa-miR-3621 and hsa-miR-665 havesignificantly reduced levels in subjects with aggressive PC compared tosubjects who do not have PC, but have BPH. Thus, the detection of areduced expression of any of these biomarkers in a subject relative to asuitable control may indicate that the subject has aggressive PC.Preferably, the control is a sample from a subject who does not have PC,but may have a different disease e.g. BPH. Preferably, the sample is abodily fluid sample (e.g. blood sample).

The inventors also found that hsa-miR-3621, hsa-miR-665, hsa-miR-1291and hsa-miR-1973 have significantly reduced levels in subjects withindolent PC compared to subjects who do not have PC, but have BPH. Thus,the detection of a reduced expression of any of these biomarkers in asubject relative to a suitable control may indicate that the subject hasindolent PC. Preferably, the sample is a bodily fluid sample (e.g. bloodsample).

The inventors also found that hsa-miR-3621, hsa-miR-183, hsa-miR-375,hsa-miR-665, hsa-miR-96, hsa-miR-663, hsa-miR-182, hsa-miR-494,hsa-miR-148a*, hsa-miR-1291, hsa-miR-602, hsa-miR-182*, hsa-miR-33b*,hsa-miR-1973, hsa-miR-153-1/hsa-miR-153-2, hsa-miR-141*, hsa-miR-1469,hsa-miR-1181 and hsa-miR-3607-5p have significantly increased levels inPC subjects compared to a sample taken from a non-PC region from thesame diseased prostate, from the same subject (see Table 1). Thus, thedetection of an increased expression of one or more of these biomarkersin a subject relative to a negative control (e.g. a non-canceroussample) may indicate that the subject has PC. Preferably, the sample isa fresh tissue sample. Preferably, the biomarker is any of the groupconsisting of: hsa-miR-3621, hsa-miR-665, hsa-miR-1291, hsa-miR-1973,hsa-miR-33b*, hsa-miR-3607-5p, hsa-miR-1181, hsa-miR-1469 andhsa-miR-602.

The inventors also found that hsa-miR-153, hsa-miR-182, hsa-miR-183,hsa-miR-183*, hsa-miR-375 and hsa-miR-96 have significantly increasedlevels in PC subjects compared to subjects who do not have PC, but havebladder cancer. Thus, the detection of an increased expression of one ormore of these biomarkers in a subject relative to a suitable control mayindicate that the subject has PC. Preferably, the control is a samplefrom a subject who does not have PC, but may have a different diseasee.g. bladder cancer. Preferably, the sample is a preserved prostatetissue sample (e.g. FFPE tissue sample). Preferably, the biomarker ishsa-miR-153 or hsa-miR-183*.

The inventors also found that hsa-miR-183*, hsa-miR-185, hsa-miR-133a-1,hsa-miR-1-1 have significantly increased levels in PC subjects comparedto subjects who do not have PC, but have BPH. Thus, the detection of anincreased expression of one or more of these biomarkers in a subjectrelative to a suitable control may indicate that the subject has PC.Preferably, the control is a sample from a subject who does not have PC,but may have a different disease e.g. BPH. Preferably, the sample is abodily fluid sample (e.g. a blood sample). The level of a particularbiomarker in a sample from a subject with aggressive PC may be above orbelow the level seen in a sample from a subject with indolent PC. Theexpression of miRNAs can either be up-regulated or down-regulateddepending on the state of the PC. In a population of subjects withindolent PC, there may thus be significant levels of miRNAs disclosed inTable 17 and these may occur at a significant frequency in thepopulation. The level and frequency of these biomarkers may be alteredin aggressive PC cohort, compared with the indolent PC cohort. Ananalysis of the level and frequency of these biomarkers in theaggressive and indolent populations may identify differences whichprovide diagnostic and prognostic information. The level of miRNAs mayincrease or decrease in an aggressive PC sample, compared with anindolent PC sample.

The inventors found that hsa-miR-133a-1/hsa-miR-133a-2, hsa-miR-133b,hsa-miR-378a, hsa-miR-99b*, hsa-miR-1-1/hsa-miR-1-2, hsa-miR-139,hsa-miR-92b and hsa-miR-582 have significantly reduced levels insubjects with aggressive PC subjects compared to subjects with indolentPC (see Table 2). Thus, the detection of a reduced expression of one ormore of these biomarkers in a subject relative to a control may indicatethat the subject has aggressive PC, or that the PC is prone to progress,recur and/or metastasize. On the other hand, the detection of anincreased expression of one or more of these biomarkers in a subjectrelative to a control may indicate that the PC is in remission. Thecontrol can be a healthy sample from the same subject, an earlier samplefrom the same subject or samples from healthy, non-PC cohort.Preferably, the sample is a fresh tissue sample. Preferably, thebiomarker is any of the group consisting of: hsa-miR-99b*, hsa-miR-133b,hsa-miR-139, hsa-miR-378a and hsa-miR-133a-1.

The inventors also found that hsa-miR-133b has significantly reducedlevels in subjects with aggressive PC compared to subjects who haveindolent PC. Thus, the detection of a reduced expression of thisbiomarker in a subject relative to a suitable control may indicate thatthe subject has aggressive PC and/or that the PC is prone to progress,recur, and/or metastasize. On the other hand, the detection of anincreased expression of this biomarker in a subject relative to asuitable control may indicate that the PC is in remission. The controlcan be a healthy sample from the same subject, an earlier sample fromthe same subject or samples from healthy, non-PC cohort. Preferably, thesample is a preserved prostate tissue sample (e.g. FFPE tissue sample).

The inventors also found that hsa-miR-3621 has significantly reducedlevels in subjects with aggressive PC compared to subjects who haveindolent PC. Thus, the detection of a reduced expression of thisbiomarker in a subject relative to a suitable control may indicate thatthe subject has aggressive PC and/or that the PC is prone to progress,recur, and/or metastasize. On the other hand, the detection of anincreased expression of this biomarker in a subject relative to asuitable control may indicate that the PC is in remission. The controlcan be a healthy sample from the same subject, an earlier sample fromthe same subject or samples from healthy, non-PC cohort. Preferably, thesample is a bodily fluid sample (e.g. a blood sample). The inventorsfound that hsa-miR-96, hsa-miR-182*, hsa-miR-449a, hsa-miR-210,hsa-miR-429, hsa-miR-188, hsa-miR-200b, hsa-miR-183 and hsa-miR-183*have significantly increased levels in subjects with aggressive PCsubjects compared to subjects with indolent PC (see Table 2). Thus, thedetection of an increased expression of one or more of these biomarkersin a subject relative to a control may indicate that the subject hasaggressive PC and/or that the PC is prone to progress, recur, and/ormetastasize. On the other hand, the detection of a reduced expression ofone or more of these biomarkers in a subject relative to a control mayindicate that the PC is in remission. The control can be a healthysample from the same subject, an earlier sample from the same subject orsamples from healthy, non-PC cohort. Preferably the sample is a freshtissue sample. Preferably, the biomarker is any of the group consistingof: hsa-miR-183*, hsa-miR-188-3p, hsa-miR-429, hsa-miR-200b,hsa-miR-182*, hsa-miR-96 and hsa-miR-183.

The inventors also found that hsa-miR-182 and hsa-miR-183 havesignificantly increased levels in subjects with aggressive PC comparedto subjects with indolent PC. Thus, the detection of an increasedexpression of any of these biomarkers in a subject relative to asuitable control may indicate that the subject has aggressive PC and/orthat the PC is prone to progress, recur, and/or metastasize. On theother hand, the detection of a reduced expression of any of thesebiomarkers in a subject relative to a suitable control may indicate thatthe PC is in remission. The control can be a healthy sample from thesame subject, an earlier sample from the same subject or samples fromhealthy, non-PC cohort. Preferably, the sample is a preserved tissuesample (e.g. FFPE tissue sample).

The inventors also found that hsa-miR-582, hsa-miR-99b*, hsa-miR-449aand hsa-miR-210 have significantly increased levels in subjects withaggressive PC compared to subjects with indolent PC. Thus, the detectionof an increased expression of any of these biomarkers in a subjectrelative to a suitable control may indicate that the subject hasaggressive PC and/or that the PC is prone to progress, recur, and/ormetastasize. On the other hand, the detection of a reduced expression ofany of these biomarkers in a subject relative to a suitable control mayindicate that the PC is in remission. The control can be a healthysample from the same subject, an earlier sample from the same subject orsamples from healthy, non-PC cohort. Preferably, the sample is a bodilyfluid sample (e.g. blood sample).

The inventors also found that hsa-miR-1291, hsa-miR-1973 andhsa-miR-449a have significantly increased levels in subjects withaggressive PC compared to subjects with indolent PC. Thus, the detectionof an increased expression of any of these biomarkers in a subjectrelative to a suitable control may indicate that the subject hasaggressive PC and/or that the PC is prone to progress, recur, and/ormetastasize. On the other hand, the detection of a reduced expression ofany of these biomarkers in a subject relative to a suitable control mayindicate that the PC is in remission. The control can be a healthysample from the same subject, an earlier sample from the same subject orsamples from healthy, non-PC cohort. Preferably, the sample is a bodilyfluid sample (e.g. blood sample).

In general, therefore, a method of the invention will involvedetermining whether a sample contains a biomarker level which isassociated with PC and/or aggressive PC. Thus a method of the inventioncan include a step of comparing biomarker levels in a subject's sampleto levels in (i) a sample from a patient with known PC disease state,e.g. indolent or aggressive PC, (ii) a sample from a patient without PC,and/or (iii) an absolute value. The comparison provides a diagnosticand/or prognostic indicator of whether the subject has PC or aggressivePC. An aberrant level of one or more biomarker(s), as compared to knownor standard expression levels of those biomarker(s) in a sample from apatient without PC, indicates that the subject has PC and/or aggressivePC.

A non-PC sample or a sample from a subject without PC can be any of: i)subject with no clinical presentation of prostate-related diseases; ii)BPH and iii) prostatitis. The non-PC sample or the sample from a subjectwithout PC sample is preferably age-matched against the test subject.The non-PC sample or the sample from a subject without PC is preferablyBPH.

The biomarkers of the invention have different relative differentialexpression profiles in a PC sample compared to a negative control. Pairsof these biomarkers (one is up-regulated and the other is down-regulatedrelative to the same control) may provide a useful way of diagnosing orpredicting PC. For example, the inventors found that hsa-miR-183 isup-regulated in PC samples vs. control and hsa-miR-221 is down-regulatedin PC samples vs. control, so this pair would be useful. This divergentbehaviour can enhance diagnosis or prediction of PC when a pair of thebiomarker is assessed in the same sample.

Thus, a method of the invention can include a step of comparing theexpression levels of a first and a second biomarker of the invention ina subject's sample, wherein the first biomarker is positively associatedwith an increased risk in PC and the second biomarker is negativelyassociated with an increased risk in PC, wherein a difference in theexpression levels between the first and second biomarkers indicates thatthe subject has PC and/or aggressive or indolent PC.

A method of the invention can include: (i) comparing the expressionlevels of a first biomarker of the invention in a subject's sample and acontrol, (ii) comparing the expression levels of a second biomarker ofthe invention in the same sample and the control, wherein the firstbiomarker is positively associated with an increased risk in PC and thesecond biomarker is negatively associated with an increased risk in PC,and (iii) comparing the determinations of (i) and (ii), wherein thecomparison provides a diagnostic indicator of whether the subject has PCor a prognostic indicator of whether the subject has PC of either theindolent or aggressive form. Preferably, the difference in the relativeexpression levels in (i) and (ii) indicates that the subject has PC,and/or aggressive or indolent PC.

Where diagnosis of PC is the primary interest, if the sample is aprostate tissue sample (e.g. a fresh tissue sample), the first biomarkercan be any of the group consisting of: hsa-miR-3621, hsa-miR-183,hsa-miR-375, hsa-miR-665, hsa-miR-96, hsa-miR-663, hsa-miR-182,hsa-miR-494, hsa-miR-148a*, hsa-miR-1291, hsa-miR-602, hsa-miR-182*,hsa-miR-33b*, hsa-miR-1973, hsa-miR-153-1/hsa-miR-153-2, hsa-miR-141*,hsa-miR-1469, hsa-miR-1181 and hsa-miR-3607-5p. Preferably, the firstbiomarker is any of the group consisting of: hsa-miR-3621, hsa-miR-665,hsa-miR-1291, hsa-miR-1973, hsa-miR-33b*, hsa-miR-3607-5p, hsa-miR-1181,hsa-miR-1469 and hsa-miR-602. The second biomarker can be hsa-miR-205 orhsa-miR-221.

When prognosis of PC is the primary interest, if the sample is aprostate tissue sample (e.g. a fresh tissue sample), the first biomarkercan be any of the group consisting of: hsa-miR-96, hsa-miR-182,hsa-miR-449a, hsa-miR-210, hsa-miR-429, hsa-miR-188, hsa-miR-200b,hsa-miR-183 and hsa-miR-183*. Preferably, the first biomarker is any ofthe group consisting of: hsa-miR-183*, hsa-miR-188-3p, hsa-miR-429,hsa-miR-200b, hsa-miR-182*, hsa-miR-96 and hsa-miR-183. The secondbiomarker can be any of the group consisting of:hsa-miR-133a-1/hsa-miR-133a-2, hsa-miR-133b, hsa-miR-378a, hsa-miR-99b*,hsa-miR-1-1/hsa-miR-1-2, hsa-miR-139, hsa-miR-92b and hsa-miR-582.Preferably, the second biomarker is any of the group consisting of:hsa-miR-99b*, hsa-miR-133b, hsa-miR-139, hsa-miR-378a andhsa-miR-133a-1/hsa-miR-133a-2.

Where diagnosis of PC is the primary interest, if the sample is a bodilyfluid (e.g. a blood sample), the first biomarker can be any of the groupconsisting of: hsa-miR-183*, hsa-miR-185, hsa-miR-133a-1, hsa-miR-1-1.The second biomarker can be any of the group consisting of: hsa-miR-665,hsa-miR-582, hsa-miR-182, hsa-miR-378a, hsa-miR-96, hsa-miR-200b,hsa-miR-191, hsa-miR-429, hsa-miR-494, hsa-miR-99b*, hsa-miR-375,hsa-miR-141, hsa-miR-148*, hsa-miR-1291, hsa-miR-1973, hsa-miR-103,hsa-miR-3607-5p, hsa-miR-133b and hsa-miR-210.

Where prognosis of PC is the primary interest, if the sample is a bodilyfluid (e.g. a blood sample), the first biomarker can be any of the groupconsisting of: hsa-miR-582, hsa-miR-99b*, hsa-miR-449a and hsa-miR-210.

Where diagnosis of PC is the primary interest, if the sample is a bodilyfluid (e.g. a blood sample), the second biomarker can be any of thegroup consisting of: hsa-miR-665, hsa-miR-3621, hsa-miR-1973,hsa-miR-1291 and hsa-miR-183. Preferably, the second biomarker is any ofthe group consisting of: hsa-miR-665, hsa-miR-3621, hsa-miR-1973 andhsa-miR-1291.

Where prognosis of PC is the primary interest, if the sample is a bodilyfluid (e.g. a blood sample), the first biomarker can be any of the groupconsisting of: hsa-miR-1291, hsa-miR-1973 and hsa-miR-449a. The secondbiomarker can be hsa-miR-3621.

Where diagnosis of PC is the primary interest, if the sample is aprostate tissue sample (e.g. a preserved tissue sample such as FFPEtissue sample), the first biomarker can be any of the group consistingof: hsa-miR-153, hsa-miR-182, hsa-miR-183, hsa-miR-183*, hsa-miR-375,hsa-miR-96. Preferably, the biomarker is hsa-miR-153 or hsa-miR-183*.Preferably, the first biomarker is hsa-miR-153 or hsa-miR-183*. Thesecond biomarker can be any of the group consisting of: hsa-miR-3621,hsa-miR-33b* and hsa-miR-1973. Where prognosis of PC is the primaryinterest, if the sample is a prostate tissue sample (e.g. a preservedtissue sample such as FFPE tissue sample), the first biomarker can behsa-miR-183 or hsa-miR-182. The second biomarker can be hsa-miR-133b.

The level of a biomarker should be different from that seen in acontrol. Advanced statistical tools can be used to determine whether twolevels are the same or different. For example, an in vitrodiagnosis/prognosis will rarely be based on comparing a singledetermination. Rather, an appropriate number of determinations will bemade with an appropriate level of accuracy to give a desired statisticalcertainty with an acceptable sensitivity and/or specificity. Levels ofmiRNAs can be measured quantitatively to permit proper comparison, andenough determinations will be made to ensure that any difference inlevels can be assigned a statistical significance to a level of p≦0.05or better. The number of determinations will vary according to variouscriteria (e.g. the degree of variation in the baseline, the degree ofup-regulation in disease states, the degree of noise, etc.) but, again,this falls within the normal design capabilities of a person of ordinaryskill in this field. For example, interquartile differences ofnormalised data can be assessed, and the threshold for a positive signal(i.e. indicating the presence or absence of a particular miRNA) can bedefined as requiring that miRNAs in a sample hybridise with thecomplementary detection probe with at least a log change +/−0.585 thanthe interquartile difference above the 75th percentile. Other criteriaare familiar to those skilled in the art and, depending on the assaysbeing used, they may be more appropriate than quantile normalisation.Other methods to normalise data include data transformation strategiesknown in the art e.g. scaling, log normalisation, median normalisation,etc.

The underlying aim of these data interpretation techniques is todistinguish between the presence of a Table 17 biomarker and of anarbitrary control biomarker, and/or to distinguish between the responseof sample from a PC and/or aggressive PC subject respectively from acontrol subject. Methods of the invention may have sensitivity of atleast, but not limited to, 50% (e.g. >50%, >55%, >60%,65%, >70%, >75%, >80%, >85%, >90%, >95%, >96%, >97%, >98%, >99%).Methods of the invention may have specificity of at least, but notlimited to, 50% (e.g. >50%, >55%, >60%,65%, >70%, >75%, >80%, >85%, >90%, >95%, >96%, >97%, >98%, >99%).

Data obtained from methods of the invention, and/or diagnostic and/orprognostic information based on those data, may be stored in a computermedium (e.g. in RAM, in non-volatile computer memory, on CD-ROM, DVD)and/or may be transmitted between computers e.g. over the Internet.

If a method of the invention indicates that a subject has PC, furthersteps may then follow. For instance, the subject may undergoconfirmatory diagnostic procedures, such as those involving physicalinspection of the subject, and/or may be treated with therapeuticagent(s) suitable for treating PC and/or aggressive PC.

If a method of the invention indicates that a subject has indolent PC,the subject will be treated with appropriate clinical treatments, e.g.active surveillance (i.e. put on a watch list).

If a method of the invention indicates that a subject has aggressive PC,the subject will be treated with appropriate clinical treatments, e.g.prostatectomy and/or chemotherapy.

Monitoring the Efficacy of Therapy

As mentioned above, some methods of the invention involve testingsamples from the same subject at two or more different points in time.In general, where the above text refers to the presence or absence ofbiomarker(s), the invention also includes an increasing or decreasinglevel of the biomarker(s) over time. Methods which determine changes inbiomarker(s) over time can be used, for instance, to monitor theefficacy of a therapy being administered to the subject (e.g. intheranostics). The therapy may be administered before the first sampleis taken, at the same time as the first sample is taken, or after thefirst sample is taken.

The invention can be used to monitor a subject who is receiving PCtherapy. Current therapies for PC include chemotherapy and/or hormonetherapy. Hormone therapy seeks to block access of dihydrotestosterone(DHT) to prostate cells or to block the effects of DHT within prostatecells. Anti-androgens are medications such as flutamide, bicalutamide,nilutamide, and cyproterone acetate which directly block the actions oftestosterone and DHT within prostate cancer cells. They may be given incombination with drugs such as ketoconazole and aminoglutethimide whichblock the production of adrenal androgens.

In related embodiments of the invention, the results of monitoring atherapy are used for future therapy prediction. For example, iftreatment with a particular therapy is effective in reducing oreliminating disease symptoms in a subject, and is also shown to decreaselevels of a particular biomarker in that subject, detection of thatbiomarker in another subject may indicate that this other subject willrespond to the same therapy. Conversely, if a particular therapy was noteffective in reducing or eliminating disease symptoms in a subject whohad a particular biomarker or biomarker profile, detection of thatbiomarker or profile in another subject may indicate that this othersubject will also fail to respond to the same therapy.

In other embodiments, the presence of a particular biomarker can be usedas the basis of proposing or initiating a particular therapy (patientstratification). For instance, if it is known that levels of aparticular miRNA can be reduced by administering a particular therapythen that miRNA's detection may suggest that the therapy should begin.Thus the invention is useful in a theranostic setting.

Normally at least one sample will be taken from a subject before atherapy begins.

Imaging and Staining

The miRNAs listed in Table 17 can be useful for imaging. A labelled,synthetic miRNA complementary to a miRNA(s) listed in Table 17, could beused for the identification, in ex vivo (e.g. tissue samples taken frombiopsies), and in vivo (e.g. magnetic resonance imaging (MRI), positronemission tomography (PET) computed tomography (CT) scans of patients)samples of miRNAs associated with PC and/or aggressive PC. This maypotentially offer a method for the early identification of PC and/oraggressive PC. Imaging techniques can also be used to monitor theprogress or remission of disease, or the impact of a therapy.

The miRNAs listed in Table 17 can be useful for analysing tissue samplesby staining e.g. using standard FISH. A fluorescently labelled miRNA,complementary in sequence to the miRNAs outlined in Table 17 can becontacted with a tissue sample to visualise the location of the miRNA. Asingle sample could be stained against multiple miRNAs, and thesedifferent miRNAs may be differentially labelled to enable them to bedistinguished. As an alternative, a plurality of different samples caneach be stained with a single, labelled miRNA.

Thus the invention provides a labelled nucleic acid which can hybridiseto miRNA(s) listed in Table 17. The miRNA may be, but not limited to, ahuman miRNA, as discussed above. Any suitable label can be used e.g.quantum dots, spin labels, fluorescent labels, dyes, etc. These labelledmiRNAs can be used in methods of in vivo and/or in vitro imaging.

microRNA-Based Therapy

The miRNAs listed in Table 17 can be useful for miRNA-based therapy,e.g., antisense therapy. There is literature precedent outlining the useof antisense therapy to manage cancer [37]. A synthetic miRNAcomplementary to a miRNA(s) listed in Table 17 could be used tostimulate cell death of cancerous cells (either associated with PCand/or aggressive PC). Additionally, in vivo antisense therapy could beused to introduce miRNA complementary to a miRNA(s) listed in Table 17to specifically bind to, and abrogate, overexpression of specificmiRNA(s) associated with PC and/or aggressive PC.

Thus the invention provides a nucleic acid which hybridises to miRNA(s)listed in Table 17 and which is conjugated to a cytotoxic agent. ThemiRNA may be, but not limited to, a human miRNA, as discussed above. Anysuitable cytotoxic agent can be used. These conjugates miRNAs can beused in methods of therapy.

Thus the invention provides a complementary miRNA which recognises amiRNA(s) listed in Table 17 for the purposes of miRNA-based therapieswhich include, but not limited to, antisense therapy.

Alternative Biomarkers

The invention has been described above by reference to miRNA biomarkers.In addition to these biomarkers, however, the invention can be used withother biological manifestations of the Table 17 miRNAs. For example, theexpression level of mRNA transcripts which are a target of a Table 17miRNA can be measured, particularly in tissues where changes intranscription level can easily be determined (such as in the potentialdisease tissue). Similarly, the copy number variation of a chromosomallocation of a Table 17 miRNA can be measured e.g. to check for achromosomal deletion or duplication events. The level of a regulator oftranscription for a Table 17 miRNA can be measured e.g. the methylationstatus of the miRNA chromosomal region.

A single pre-miRNA precursor may lead to one or more mature miRNAsequences, such as sequences excised from the 5′ and 3′ arms of thehairpin, as shown in Table 18. The invention can be used to look forother mature miRNA sequences from the same pre-miRNA precursor. Forexample, other mature miRNA sequences from the same precursor in Table18 may be appropriate biomarkers as well.

Further possibilities will be apparent to the skilled reader.

Preferred Panels

Preferred embodiments of the invention are based on a panel ofbiomarkers. Panels of particular interest for the diagnosis of PCconsist of or comprise the combinations of biomarkers listed in Tables 3to 9 (which show seven panels of 1, 2, 3, 4, 5, 6 and 7). Panels ofparticular interest for the prognosis of aggressive PC consist of orcomprise the combinations of biomarkers listed in Tables 10 to 16 (whichshow seven panels of 1, 2, 3, 4, 5, 6 and 7).

The seven different panels listed in each of Tables 3 to 9 and Tables 10to 16 can be expanded by adding further biomarker(s) to create a largerpanel. The further biomarkers can usefully be selected from knownbiomarkers (such as PSA, PCA3, DD3, AMACR, EPCA, EPCA-2, sarcosine,etc.; see above), from Table 17, or from Table 1, or from Table 2 whereappropriate. In general the addition does not decrease the sensitivityor specificity of the panel shown in the Tables.

Such panels include, but are not limited to:

-   -   A panel comprising a biomarker selected from Table 3.    -   A panel comprising a biomarker selected from Table 10.    -   A panel comprising or consisting of 2 different biomarkers,        namely: (i) a biomarker selected from Table 3 and (ii) a further        biomarker selected from Table 1.    -   A panel comprising or consisting of 2 different biomarkers,        namely: (i) a biomarker selected from Table 3 and (ii) a further        biomarker selected from Table 2.    -   A panel comprising or consisting of 2 different biomarkers,        namely: (i) a biomarker selected from Table 10 and (ii) a        further biomarker selected from Table 2.    -   A panel comprising or consisting of 2 different biomarkers,        namely: (i) a biomarker selected from Table 10 and (ii) a        further biomarker selected from Table 1.    -   A panel comprising or consisting of 3 different biomarkers,        namely: (i) a group of 2 biomarkers selected from Table 4        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 3 different biomarkers,        namely: (i) a group of 2 biomarkers selected from Table 4        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 3 different biomarkers,        namely: (i) a group of 2 biomarkers selected from Table 11        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 3 different biomarkers,        namely: (i) a group of 2 biomarkers selected from Table 11        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 4 different biomarkers,        namely: (i) a group of 3 biomarkers selected from Table 5        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 4 different biomarkers,        namely: (i) a group of 3 biomarkers selected from Table 5        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 4 different biomarkers,        namely: (i) a group of 3 biomarkers selected from Table 12        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 4 different biomarkers,        namely: (i) a group of 3 biomarkers selected from Table 12        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 5 different biomarkers,        namely: (i) a group of 4 biomarkers selected from Table 6        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 5 different biomarkers,        namely: (i) a group of 4 biomarkers selected from Table 6        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 5 different biomarkers,        namely: (i) a group of 4 biomarkers selected from Table 13        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 5 different biomarkers,        namely: (i) a group of 4 biomarkers selected from Table 13        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 6 different biomarkers,        namely: (i) a group of 5 biomarkers selected from Table 7        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 6 different biomarkers,        namely: (i) a group of 5 biomarkers selected from Table 7        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 6 different biomarkers,        namely: (i) a group of 5 biomarkers selected from Table 14        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 6 different biomarkers,        namely: (i) a group of 5 biomarkers selected from Table 14        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 7 different biomarkers,        namely: (i) a group of 6 biomarkers selected from Table 8        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of 7 different biomarkers,        namely: (i) a group of 6 biomarkers selected from Table 8        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 7 different biomarkers,        namely: (i) a group of 6 biomarkers selected from Table 15        and (ii) a further biomarker selected from Table 2.    -   A panel comprising or consisting of 7 different biomarkers,        namely: (i) a group of 6 biomarkers selected from Table 15        and (ii) a further biomarker selected from Table 1.    -   A panel comprising or consisting of a group of 7 different        biomarkers selected from Table 9. This panel is particularly        useful for diagnosis.    -   A panel comprising or consisting of a group of 7 different        biomarkers selected from Table 16. This panel is particularly        useful for prognosis.

Preferred panels have between 1 and 7 biomarkers in total.

General

The term “comprising” encompasses “including” as well as “consisting”e.g. a composition “comprising” X may consist exclusively of X or mayinclude something additional e.g. X+Y.

References to a miRNA's ability to “hybridise” to a complementaryoligonucleotide probe means that the miRNA and the complementaryoligonucleotide probe interact strongly enough to withstand standardwashing procedures in the assay in question. Thus non-specific bindingwill be minimised or eliminated.

References to a “level” of a biomarker mean the amount of an analyte(e.g. a miRNA) measured in a sample and this encompasses relative andabsolute concentrations of the analyte, analyte titres, relationships toa threshold, rankings, percentiles, etc.

An assay's “sensitivity” is the proportion of true positives which arecorrectly identified i.e. the proportion of PC subjects who testpositive by a method of the invention. This can apply to individualbiomarkers, panels of biomarkers, single assays or assays which combinedata integrated from multiple sources e.g. PSA score and DRE. It canrelate to the ability of a method to identify samples containing aspecific analyte (e.g. miRNAs) or to the ability of a method tocorrectly identify samples from subjects with PC.

An assay's “specificity” is the proportion of true negatives which arecorrectly identified i.e. the proportion of subjects without PC who testnegative by a method of the invention. This can apply to individualbiomarkers, panels of biomarkers, single assays or assays which combinedata integrated from multiple sources e.g. PSA score and DRE. It canrelate to the ability of a method to identify samples containing aspecific analyte (e.g. miRNAs) or to the ability of a method tocorrectly identify samples from subjects with PC.

Unless specifically stated, a method comprising a step of mixing two ormore components does not require any specific order of mixing. Thuscomponents can be mixed in any order. Where there are three componentsthen two components can be combined with each other, and then thecombination may be combined with the third component, etc.

References to a percentage sequence identity between two miRNA sequencesmeans that, when aligned, that percentage of nucleotides are the same incomparing the two sequences. This alignment and the percent homology orsequence identity can be determined using software programs known in theart, for example those described in section 7.7.18 of ref. 38. Apreferred alignment is determined by the Smith-Waterman homology searchalgorithm using an affine gap search with a gap open penalty of 12 and agap extension penalty of 2, BLOSUM matrix of 62. The Smith-Watermanhomology search algorithm is disclosed in ref. 39.

In all embodiments of the invention, where only one biomarker is used,the biomarker is preferably not hsa-miR-205, hsa-miR-183, hsa-miR-182*,hsa-miR-182, hsa-miR-449a, hsa-miR-210, hsa-miR-96 or hsa-miR-375. Inall embodiments of the invention, where a panel comprises any of:hsa-miR-205, hsa-miR-183, hsa-miR-182*, hsa-miR-182, hsa-miR-449a,hsa-miR-210, hsa-miR-96 and hsa-miR-375, preferably the panel furthercomprises one or more biomarkers from Table 17 that is not any ofhsa-miR-205, hsa-miR-183, hsa-miR-182*, hsa-miR-182, hsa-miR-449a,hsa-miR-210, hsa-miR-96 and hsa-miR-375.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a hierarchical plot showing clustering of miRNAs according tothe type of tissue (i.e. disease v. normal).

FIG. 2 is a box-plot showing fold-changes of 9 miRNAs in PC samplesrelative to non-PC samples. Left to right (in pairs): hsa-miR183,hsa-miR183*, hsa-miR-205, hsa-miR-222, hsa-miR-224, hsa-miR-23b*,hsa-miR-31, hsa-miR-31* and hsa-miR-96. Left of the pair: normal/healthysamples, right of the pair: PC samples. Unpaired t-test: P<0.01; foldchange>3.

FIG. 3 is a box plot showing fold-changes of 7 miRNAs in normal/healthysamples, indolent samples and aggressive samples. The intensity isnormalised across all samples for the 7 markers. Left to right (inquintets): hsa-miR-31, hsa-miR-221, hsa-miR-222, hsa-miR-181b,hsa-miR-182, hsa-miR-183 and hsa-miR-375. Quintet from left to right:Gleason scores: 0+0, 3+3, 3+4, 4+3 and 4+5. Normal/healthy samplesbinned as 0+0, indolent samples binned as 3+3 and 3+4, and aggressivesamples binned as 4+3 and 4+5.

FIGS. 4-11 are box-plots showing the relative expression profiles ofvarious miRNAs between Gleason 6 (indolent PC) samples, Gleason 8(aggressive PC) samples and PC negative samples (prostate samplesderived from a subject with bladder cancer, but not prostate cancer).The miRNA analysed are: hsa-miR-3621 (FIG. 4), hsa-miR-33b* (FIG. 5),hsa-miR-182 (FIG. 6), hsa-miR-1973 (FIG. 7), hsa-miR-183* (FIG. 8),hsa-miR-153-1/hsa-miR-153-2 (FIG. 9), hsa-miR-96 (FIG. 10) andhsa-miR-133b (FIG. 11). “Gleason 6 (A)” denotes the primary cancerregion in the Gleason 6 (indolent) PC sample; “Gleason 6 (E)” denotes anexclusively non-cancerous region in the Gleason 6 (indolent) PC sample;“Gleason 8 (A)” denotes a primary cancer region in the Gleason 8(aggressive) PC sample; “Gleason 8 (E)” denotes an exclusivelynon-cancerous region in the Gleason 8 (aggressive) PC sample.

MODES FOR CARRYING OUT THE INVENTION Array Preparation

For microarray fabrication and usage, Agilent Technologies' (“Agilent”)miRNA microarray was used. The content of the microarray is continuouslyaligned with releases from the miRBase database [14, 15, 16, 17],representing all known miRNAs from human beings, as well as all knowhuman viral miRNAs. These arrays are printed using Agilent's ink-jet insitu synthesis microarray fabrication machines.

Biomarker Confirmation

Tissue samples were obtained from radical prostatectomy, and dividedinto tissue slices. Within any given slice, there may be areas of cancer(“disease”) surrounded by non-cancerous tissue (“non-disease”). Theaggressive and indolent samples were identified based on Gleason scores:indolent is defined as a Gleason score ≦3+4, and aggressive is definedas a Gleason score ≧4+3. Using these tissue slices two groups of sampleswere used:

-   -   1. disease tissue (n=83).    -   2. non-disease tissue (n=45).

The tissue slices were homogenised and total RNA extracted and miRNAenriched using standard column filtration methodologies, which are wellknown in the art. Tissue samples from both groups were individuallyanalysed using the Agilent miRNA microarray (G4870A-031181), accordingto their standard protocol, (manual part number G4170-90011, version2.4). However, deviations from the standard protocol included labellingof the samples using 2.25 μl Cyanine 3-pCp, and hybridising themicroarray slides for 44 hours.

The probed and dried arrays were then scanned using a microarray scannercapable of using an excitation wavelength suitable for the detection ofthe labelled miRNAs, and to determine magnitude of miRNA binding to thecomplementary detection probe. The microarray scans produced images foreach array that were used to determine the intensity of fluorescencebound to each oligonucleotide spot which were used to normalise andscore array data.

The raw microarray scan image contains raw signal intensity (alsoreferred to as the relative fluorescent unit, RFU) for eacholigonucleotide spot (also referred to as a feature) on the array. Theseimages were then feature extracted using Agilent's proprietary featureextraction software. Alternative analyses use other measures of spotintensity such as the mean fluorescence, total fluorescence, as known inthe art.

The resulting average intensities of all oligonucleotide features oneach array were then normalised to reduce the influence of technicalbias (e.g. laser power variation, surface variation, input miRNAconcentration, etc.) by a percentile normalisation procedure. Othermethods for data normalisation suitable for the data include, amongstothers, quantile normalisation [31]. Such normalisation methods areknown in the art of microarray analysis.

Logistic regression, with optimisation for S+S was applied to allcombinations of markers exceeding defined cut-offs for statisticalsignificance and fold change. The number of biomarkers in each panel waslimited to n where n=1−7. The performance of the derived panels was thenranked by combined S+S.

The hierarchical clustering of miRNAs according to the type of tissue(i.e. disease v. normal) is shown in FIG. 1. FIG. 2 shows expression ofmiRNAs in PC samples and non-PC samples. FIG. 3 shows expression ofmiRNAs in normal/healthy samples, indolent samples and aggressivesamples.

Biomarkers from Plasma and Serum Samples

It is known that miRNA biomarkers can be found in plasma or serum ofcancer patient samples (e.g. references 40,41, etc.). The inventorstherefore investigated the diagnostic and/or prognostic potential of asubset of the miRNA biomarkers from Tables 1 and 2 for identifying PC inserum and plasma samples.

A set of fifty (50) prostate cancer plasma samples (9×Normal (BPH;age-matched controls); 27×Gleason 6; and 14×Gleason 8) were investigatedto assess whether the miRNA markers described herein had biologicalutility within a different biological specimen (i.e. human plasma).

Additionally, a further set of sixty-seven (67) prostate cancer serumsamples (31×Normal (age-matched controls); 31×Gleason 6; and 5×Gleason8) were investigated to assess whether the miRNA markers describedherein had biological utility within human serum.

Both the plasma and serum samples were ethically obtained from Caucasianmale donors whom had been clinically assessed for their disease status.The plasma samples defined as “normal [BPH]” were classified as suchbased on the donor's absence of clinical symptoms associated with PC,but these donors still exhibited clinical indications associated withprostate dysfunction. For the serum samples defined as “normal”, thesewere classified as such based on the donor's absence of clinicalsymptoms associated with PC. Both sets of normal samples were closelyage matched (+/−5 years) to the ages of the cancer (Gleason 6 andGleason 8) samples. For both the plasma and serum samples, the samplesdefined as Gleason 8 (aggressive) and Gleason 6 (indolent) were alsoclassified by clinical assessment (e.g. biopsy, DRE etc.) and the donorswere determined to have symptoms associated with PC.

All the plasma and serum samples were processed to extract total RNA,including the small RNA fraction (<20 nt), using standard columnfiltration methodologies, which are well known in the art. Serum samplesfrom all three groups were analysed using the Life Technologies' miRNATaqMan procedure [42] with a starting concentration for all samples of30 ng/μl. Briefly, the procedure involved a reverse transcription step,followed by a 12-cycle pre-amplification step, and then subsequentlyreal-time PCR (40 cycles).

Further information about the miRNA TaqMan assays are detailed in Table19.

The raw signal intensities from the qPCR traces for each TaqMan miRNAassay were statistically analysed using methodologies known in the art.For the plasma samples, the resulting P-values and log fold changes areshown in Table 20, with a P-value <0.05 and/or a log fold change+/−0.585 being considered statistically significant. The differentialexpression profiles of the plasma miRNA markers were compared to thedifferential expression profiles of the miRNA markers previouslyidentified in fresh PC tissue. The data in Table 20 demonstrate thatthere is good concordance in the miRNA expression profiles of PC plasmasamples when compared to fresh PC tissues. This subset of miRNAs,derived from PC plasma, are also statistically significant fordetermining aggressive PC from all other sample types (i.e. indolent PCand normal), which again correlates with the fresh PC tissue data.

For the serum samples, the resulting P-values and log fold changes areshown in Table 21, with a P-value <0.05 and/or a log fold change+/−0.585 being considered statistically significant. The differentialexpression profiles of the serum miRNA markers were compared to thedifferential expression profiles of the miRNA markers previouslyidentified in fresh PC tissue. The data in Table 21 demonstrate thatthere is good concordance in the miRNA expression profile of PC serumsamples when compared to fresh PC tissues. This subset of miRNAs,derived from PC serum, is also statistically significant for determiningPC from non-PC samples, which again correlates with the fresh PC tissuedata. The inventors have therefore identified miRNA biomarkers that canbe used in panels to provide a ‘molecular signature’ to successfullydistinguish PC from non-PC, as well as aggressive PC from indolent PC,with a high degree of sensitivity and specificity, from various types ofsamples: tissues, plasma and serum samples.

Biomarkers from Plasma Samples

Table 25 provides analysis of the differential expression levels of themiRNAs of the invention in PC plasma samples compared to non-PC (BPH)plasma sample. The same sample set as the plasma experiment describedabove is used.

Table 26 provides analysis of the differential expression levels of themiRNAs of the invention in PC serum samples compared to non-PC (BPH)serum sample. The same sample set as the serum experiment describedabove is used.

Table shows plasma data with metrics (sensitivity and specificityscores, as well as area under the curve [AUC] scores) for two data sets:May 2013 (first data set) and October 2013 (second data set). The May2013 data set used balanced sample numbers of Control, Gleason 6 andGleason 8 samples to create a list of significant markers for both logfold change (≧0.585) and statistical significance (p-value, ≧0.05);using this data a statistical algorithm was trained. The algorithm wasthen tested on the subsequent data set (October 2013) to see if the datacould be ‘called’ correctly. Therefore, the data, and ultimately thelist of panel markers, is ordered by the AUC value for October 2013. Thelist of panels only contains miRNA markers that were significant betweenthe two, independent data sets.

Biomarkers of the Invention Demonstrate “Field Effect”

The expression levels of the miRNA biomarkers listed in Table 23 wereanalysed in formalin-fixed paraffin-embedded (FFPE) PC samples.

The inventors also tested whether the miRNA biomarkers of the inventionshow a ‘field-effect’ within prostate tissue. The concept of‘field-effect’ within cancer dates back to the early 1950s whenSlaughter et al. [43] described the phenomenon of abnormal tissuesurrounding the primary site of oral squamous cell carcinoma. Sincethen, various researchers have demonstrated cancer field-effect within avariety of different tissues and organs, and that this field-effect hasbeen attributed, in part, to aberrant DNA methylation in various gene(s)(e.g. 44, 45, 46).

A set of nine Gleason 8 PC formalin-fixed paraffin-embedded (FFPE)samples; eleven Gleason 6 PC FFPE samples; and ten bladder cancer FFPEsamples (negative for PC) were investigated.

The FFPE samples were ethically obtained from Caucasian male donors whomhad undergone radical prostatectomy to remove their entire prostate dueto the presence of cancer. The prostate was then clinically assessed,using histopathology, to confirm their disease status. The PC samplesused herein were either defined as Gleason 8 (aggressive) or Gleason 6(indolent). The FFPE samples defined as “PC negative” [bladder cancer]were derived from prostate removed from the patient due to the presenceof bladder cancer. However, histopathological analysis confirmed theabsence of PC from these prostates.

All the FFPE samples used herein were histopathologically sectioned andstained, using hematoxylin and eosin stain, according to methodologieswell known in the art. The stained sections were used to identify areasof aggressive/indolent PC (dependent on the patient in question) as wellas areas of non-cancerous tissue; all areas being situated in theperipheral, glandular regions of the prostate. From any given FFPEsection, five areas were marked up for subsequent macro-dissection: Area‘A’ was the primary cancer region; areas B-D were either a secondarycancer region (with a lower Gleason score, compared to the primarycancer foci) or a non-cancerous region (dependent on the patient inquestion); and area ‘E’ was exclusively a non-cancerous region.

Once suitable areas had been determined, adjacent slices were taken, theareas macro-dissected, and the FFPE samples processed to extract totalRNA, including the small RNA fraction (<20 nt), using standard columnfiltration methodologies, which are well known in the art. FFPE samplesfrom all three cohorts were analysed using the Life Technologies' miRNATaqMan procedure (manual part number 4465407, revision date 30 Mar. 2012(Rev. B)) with a starting concentration for all samples of 50 ng/μl.Briefly, the procedure involved a reverse transcription step, followedby a 12-cycle pre-amplification step, and then subsequently thereal-time PCR reaction (40 cycles).

The raw signal intensities from the qPCR traces for each TaqMan miRNAassay were normalised and statistically analysed using methodologiesknown in the art. Normalisation of the data could include, but is notlimited to, the use of normaliser miRNAs. The normaliser miRNAs wouldhave non-differential expression profiles in the same sample type.

The resulting P-values and log fold changes were determined, with a Pvalue <0.05 and a log fold change +/−0.585 being consideredstatistically significant. Examples of the comparison of thedifferential expression profile of the FFPE miRNA markers for ‘Gleason 6(A) vs PC negative’; ‘Gleason 6 (A) vs Gleason 6 (E)’; ‘Gleason 8 (A) vsPC negative’; ‘Gleason 8 (A) vs Gleason 8 (E)’; ‘Gleason 8 (A) vsGleason 6 (A)’; ‘Gleason 6 (E) vs PC negative’; and ‘Gleason 8 (E) vs PCnegative’ for the various biomarkers are shown in FIGS. 4-11.

Referring to FIG. 4, hsa-miR-3621 shows significant differentialexpression between Gleason 6 (A) samples vs PC negative samples; andGleason 8 (A) samples vs PC negative samples. This demonstrates thathsa-miR-3621 can significantly stratify PC from PC negative samples.Furthermore, there is a significant differential expression ofhsa-miR-3621 between Gleason 6 (E) samples and PC negative samples; andGleason 8 (E) samples and PC negative samples. Additionally,hsa-miR-3621 shows non-significant expression between Gleason 6 (A)samples vs Gleason 6 (E) samples; and Gleason 8 (A) samples vs Gleason 8(E) samples. This demonstrates a hsa-miR-3621-based field-effectsuggesting that any part of the prostate can be sampled (e.g. during abiopsy procedure) and the expression profile can stratify PC from PCnegative samples.

Referring to FIG. 5, hsa-miR-33b* shows significant differentialexpression between Gleason 6 (A) samples and PC negative samples; andGleason 8 (A) samples and PC negative samples. This demonstrates thathsa-miR-33b* can significantly stratify PC from PC negative samples.Furthermore, there is a significant differential expression ofhsa-miR-33b* between Gleason 6 (E) samples vs PC negative samples; andGleason 8 (E) samples vs PC negative samples. Additionally, hsa-miR-33b*shows non-significant expression between Gleason 6 (A) samples vsGleason 6 (E) samples; and Gleason 8 (A) samples vs Gleason 8 (E)samples. This demonstrates a hsa-miR 33b*-based field-effect suggestingthat any part of the prostate can be sampled (e.g. during a biopsyprocedure) and the expression profile can stratify PC from PC negativesamples.

Referring to FIG. 6, hsa-miR-182 shows significant differentialexpression between Gleason 6 (A) samples vs PC negative samples; andGleason 8 (A) samples vs PC negative samples. This demonstrates thathsa-miR-182 can significantly stratify PC from PC negative samples.Additionally, there is a significant differential expression ofhsa-miR-182 between Gleason 8 (A) samples vs Gleason 6 (A) samples, thusdemonstrating that hsa-miR-182 can significantly stratify aggressive PCfrom indolent PC. Furthermore, there is a significant differentialexpression of hsa-miR-182 between Gleason 6 (E) samples vs PC negativesamples; and Gleason 8 (E) samples vs PC negative samples. In addition,hsa-miR-182 shows non-significant expression between Gleason 6 (A)samples vs Gleason 6 (E) samples; and Gleason 8 (A) samples vs Gleason 8(E) samples. This demonstrates a hsa-miR-182-based field-effectsuggesting that any part of the prostate can be sampled (e.g. during abiopsy procedure) and the expression profile can stratify PC from PCnegative samples, as well as aggressive PC from indolent PC.

Referring to FIG. 7, hsa-miR-1973 shows significant differentialexpression between Gleason 6 (A) samples vs PC negative samples, thusdemonstrating that hsa-miR-1973 can significantly stratify indolent PCfrom PC negative samples. Furthermore, there is a significantdifferential expression of miR-1973 between Gleason 6 (E) samples vs PCnegative samples. In addition, hsa-miR-1973 shows non-significantexpression between Gleason 6 (A) samples vs Gleason 6 (E) samples. Thisdemonstrates a hsa-miR-1973-based field-effect suggesting that any partof the prostate can be sampled (e.g. during a biopsy procedure) and theexpression profile can stratify indolent PC from PC negative samples.

Referring to FIG. 8, hsa-miR-183* shows significant differentialexpression between Gleason 8 (A) samples vs PC negative samples. Thisdemonstrates that hsa-miR-183* can significantly stratify aggressive PCfrom PC negative samples. Additionally, there is a non-significantexpression of hsa-miR-183* between Gleason 8 (A) samples vs Gleason 8(E) samples. This demonstrates a hsa-miR 183*-based field-effectsuggesting that any part of the prostate can be sampled (e.g. during abiopsy procedure) to determine the absence of aggressive PC within theorgan.

Referring to FIG. 9, hsa-miR-153-1/hsa-miR-153-2 shows significantdifferential expression between Gleason 6 (A) samples vs PC negativesamples; and Gleason 8 (A) samples vs PC negative samples. Thisdemonstrates that hsa-miR-153-1/hsa-miR-153-2 can significantly stratifyPC from PC negative samples. Additionally, there is a significantdifferential expression of hsa-miR-153-1/hsa-miR-153-2 between Gleason 8(A) samples vs Gleason 8 (E) samples, thus demonstrating a potentialaggressive marker, but that the biopsy procedure would need to sampledirectly from the cancerous foci.

Referring to FIG. 10, hsa-miR-96 shows significant differentialexpression between Gleason 6 (A) samples vs PC negative samples; andGleason 8 (A) samples vs PC negative samples, thus demonstrating thathsa-miR-96 can significantly stratify PC from PC negative samples.Additionally, there is a significant differential expression ofhsa-miR-96 between Gleason 8 (A) samples vs Gleason 8 (E) samples, thusdemonstrating a potential aggressive marker, but that the biopsyprocedure would need to sample directly from the cancerous foci.

Referring to FIG. 11, hsa-miR-133b shows significant differentialexpression between Gleason 8 (A) samples vs PC negative samples; andGleason 8 (A) samples vs Gleason 6 (A) samples. This demonstrates thathsa-miR-133b can significantly stratify aggressive PC from PC negativesamples, as well as stratifying aggressive PC from indolent PC.Additionally, there is a significant differential expression ofhsa-miR-133b between Gleason 8 (A) samples vs Gleason 8 (E) samples,thus demonstrating a potential aggressive marker, but that the biopsyprocedure would need to sample directly from the cancerous foci.

hsa-miR-1-1/hsa-miR-1-2 and hsa-miR-99b* both show significantdifferential expression between Gleason 8 (A) samples vs Gleason 8 (E)samples, thus demonstrating that they are potential aggressive markers.

hsa-miR-141 shows significant differential expression between Gleason 8(A) samples vs PC negative samples, demonstrating that hsa-miR-141 cansignificantly stratify aggressive PC from PC negative samples.

hsa-miR-183 shows significant differential expression between Gleason 6(A) samples vs PC negative samples; and Gleason 8 (A) samples vs PCnegative samples. This demonstrates that hsa-miR-183 can significantlystratify PC from PC negative samples. Additionally, hsa-miR-183demonstrates a significant differential expression between Gleason 8 (A)samples vs Gleason 8 (E) samples, thus demonstrating a potentialaggressive marker, but that the biopsy procedure would need to sampledirectly from the cancerous foci. Additionally, hsa-miR-183 showssignificant differential expression between Gleason 8 (A) samples vsGleason 6 (A) samples, thus demonstrating that hsa-miR-183 cansignificantly stratify aggressive PC from indolent PC.

hsa-miR-375 shows significant differential expression between Gleason 6(A) samples vs PC negative samples; and Gleason 8 (A) samples vs PCnegative samples. This demonstrates that hsa-miR-375 can significantlystratify PC from PC negative samples

hsa-miR-494 shows significant differential expression between Gleason 6(E) samples vs PC negative samples, suggesting a hsa-miR-494-basedfield-effect suggesting that any part of the prostate can be sampled(e.g. during a biopsy procedure) to determine the absence of aggressivePC within the organ.

hsa-miR-582 and hsa-miR-1291 both show significant differentialexpression between Gleason 8 (E) samples vs PC negative samples,suggesting a hsa-miR-582-based field-effect suggesting that any part ofthe prostate can be sampled (e.g. during a biopsy procedure) todetermine the absence of aggressive PC within the organ.

hsa-miR-133a-1/hsa-miR-133a-2 shows significant differential expressionbetween Gleason 8 (A) samples vs Gleason 8 (E) samples, suggesting thatthis is a potential aggressive PC marker.

hsa-miR-182* shows significant differential expression between Gleason 8(A) samples vs Gleason 8 (E) samples, Gleason 6 (E) samples vs PCnegative samples and Gleason 8 (E) samples vs PC negative samples. Thisdemonstrates a hsa-miR-182*-based field-effect suggesting that any partof the prostate can be sampled (e.g. during a biopsy procedure) todetermine the absence of aggressive PC within the organ.

Accordingly, the inventors have identified a miRNA-based field-effectwithin prostate tissue that has the ability, due to the specific miRNAmolecular pattern as described herein, to distinguish PC from non-PC, aswell as aggressive PC from indolent PC in FFPE samples. Thus, thisallows identification or predication of PC in a generalised, lesstargeted, sampling of the prostate during a routine biopsy procedure.

It will be understood that the invention has been described by way ofexample only and modifications may be made whilst remaining within thescope and spirit of the invention.

TABLE 1 Biomarkers useful with the inventionTable 1 lists biomarkers useful with the invention, for comparing samples from PC “case”andnon-PC “control”. The measured biomarker(s) can be (i) up-regulated (an increase in fold-change, when compared to control samples) or (ii) down-regulated (a decrease in fold-change,when compared to control samples). miRNA name^((i)) SequenceSymbol^((ii)) No.^((iii)) HGNC^((iv)) Expression^((v)) hsa-miR-CGCGGGUCGGGGUCUGCAGG MIR3621 1 38930 UP 3621 hsa-miR-ACCAGGAGGCUGAGGCCCCU MIR665 7 33662 UP 665 hsa-miR-AGCUACAUUGUCUGCUGGGUUUC MIR221 3 31601 DOWN 221 hsa-miR-UAUGGCACUGGUAGAAUUCACU MIR183 4 31554 UP 183 hsa-miR-UUUGUUCGUUCGGCUCGCGUGA MIR375 6 31868 UP 375 hsa-miR-96UUUGGCACUAGCACAUUUUUGCU MIR96 8 31648 UP hsa-miR- AGGCGGGGCGCCGCGGGACCGCMIR663A 10 32919 UP 663 hsa-miR- UUUGGCAAUGGUAGAACUCACACU MIR182 1131553 UP 182 hsa-miR- UGAAACAUACACGGGAAACCUC MIR494 13 32084 UP 494hsa-miR- AAAGUUCUGAGACACUCCGACU MIR148A 14 31535 UP 148a* hsa-miR-UGGCCCUGACUGAAGACCAGCAGU MIR1291 16 35284 UP 1291 hsa-miR-GACACGGGCGACAGCUGCGGCCC MIR602 17 32858 UP 602 hsa-miR-UGGUUCUAGACUUGCCAACUA MIR182 12 31553 UP 182* hsa-miR-CAGUGCCUCGGCAGUGCAGCCC MIR33B 19 32791 UP 33b* hsa-miR-ACCGUGCAAAGGUAGCAUA MIR1973 20 37061 UP 1973 hsa-miR-UUGCAUAGUCACAAAAGUGAUC MIR153-1/ 21  31539/ UP 153-1/ MIR153-2 31540hsa-miR- 153-2 hsa-miR- CAUCUUCCAGUACAGUGUUGGA MIR141 22 31528 UP 141*hsa-miR- CUCGGCGCGGGGCGCGGGCUCC MIR1469 24 35378 UP 1469 hsa-miR-UCCUUCAUUCCACCGGAGUCUG MIR205 25 31583 DOWN 205 hsa-miR-CCGUCGCCGCCACCCGAGCCG MIR1181 27 35262 UP 1181 hsa-miR-GCAUGUGAUGAAGCAAAUCAGU MIR3607 28 38900 UP 3607-5p

Columns (Tables 1 & 2)

(i) The “miRNA name” column gives the name of the human miRNA asprovided by the specialist database, miRBase, according to version 16(released, August 2010).

(ii) The “Symbol” column gives the gene symbol which has been approvedby the Human Genome Organisation (HUGO) Gene Nomenclature Committee(HGNC). The symbol thus identifies a unique human gene. Inclusion on toHUGO is for human genes only. An additional dash-number suffix indicatespre-miRNAs that lead to identical mature miRNAs but that are located atdifferent places in the genome.

(iii) The SEQ ID NO: for the sequence of the mature, expressed miRNAbiomarker, as shown in Table 18.

(iv) The HGNC aims to give unique and meaningful names to every miRNA(and human gene). The HGNC number thus identifies a unique human gene.Inclusion on to HUGO is for human genes only.

(v) This indicates whether the miRNA is up-regulated (an increase infold-change, e.g. at least about 1.5 fold change, when compared tocontrol samples) or down-regulated (a decrease in fold-change, e.g. atleast about 1.5 fold change, when compared to control samples. For Table1, the control is non-PC. For Table 2, the control is indolent PC.

TABLE 2 Biomarkers useful with the inventionTable 2 lists biomarkers useful with the invention, for comparing samples from aggressive PC“case”and indolent PC “control”. The measured biomarker(s) can be (i) up-regulated (anincrease in fold-change, when compared to control samples) or (ii) down-regulated (a decreasein fold-change, when compared to control samples). miRNA name^((i))Sequence Symbol^((ii)) No.^((iii)) HGNC^((iv)) Expression^((v))hsa-miR-183 UAUGGCACUGGUAGAAU MIR183 4 31554 UP UCACU hsa-miR-96UUUGGCACUAGCACAUU MIR96 8 31648 UP UUUGCU hsa-miR-182* UGGUUCUAGACUUGCCAMIR182 12 31553 UP ACUA hsa-miR-449a UGGCAGUGUAUUGUUAG MIR449A 30 27645UP CUGGU hsa-miR-133a-1/ UUUGGUCCCCUUCAACCA MIR133A1/ 31  31517/ DOWNhsa-miR-133a-2 GCUG MIR133A2 31518 hsa-miR-133b UUUGGUCCCCUUCAACCAMIR133B 32 31759 DOWN GCUA hsa-miR-210 CUGUGCGUGUGACAGCG MIR210 33 31587UP GCUGA hsa-miR-378a ACUGGACUUGGAGUCAG MIR378A 35 31871 DOWN AAGGhsa-miR-99b* CAAGCUCGUGUCUGUGG MIR99B 37 31651 DOWN GUCCG hsa-miR-1-1/UGGAAUGUAAAGAAGUA MIR1-1/ 38  31499/ DOWN hsa-miR-1-2 UGUAU MIR1-2 31500hsa-miR-429 UAAUACUGUCUGGUAAA MIR429 39 13784 UP ACCGU hsa-miR-139GGAGACGCGGCCCUGUU MIR139 41 31526 DOWN GGAGU hsa-miR-188CUCCCACAUGCAGGGUU MIR188 43 31559 UP UGCA hsa-miR-92b UAUUGCACUCGUCCCGGMIR92B 45 32920 DOWN CCUCC hsa-miR-582 UAACUGGUUGAACAACU MIR582 47 32838DOWN GAACC hsa-miR-200b UAAUACUGCCUGGUAAU MIR200B 49 31579 UP GAUGAhsa-miR-183* GUGAAUUACCGAAGGGC MIR183 5 31554 UP CAUAA

Panel Data (Tables 3 to 9): Disease Vs Non-Disease

Table 3-9 list biomarkers or panels of biomarkers useful with theinvention, for comparing samples from PC “case” and non-PC “control”.The measured biomarker(s) can be (i) up-regulated (an increase infold-change, when compared to control samples) or (ii) down-regulated (adecrease in fold-change, when compared to control samples).

Columns (Tables 3 to 9)

-   -   (i) The symbol for the relevant biomarker (or, for Tables 4-9,        biomarkers in the panel).    -   (ii) S+S is the sum of the sensitivity and specificity columns.        These final two columns show the sensitivity and specificity of        a test based solely on the relevant biomarker (or, for Tables        4-9, panel) shown in the left-hand column when applied to the        samples used in the examples.

TABLE 3 Biomarker^((i)) S + S^((ii)) Sensitivity Specificityhsa-miR-3621 1.62 82.46% 79.41% hsa-miR-665 1.49 84.21% 64.71%hsa-miR-33b* 1.43 63.16% 79.41% hsa-miR-602 1.41 82.46% 58.82%hsa-miR-3607-5p 1.36 85.96% 50.00% hsa-miR-205 1.34 66.67% 67.65%hsa-miR-1973 1.33 73.68% 58.82% hsa-miR-663 1.32 82.46% 50.00%hsa-miR-1469 1.31 45.61% 85.29% hsa-miR-183 1.31 89.47% 41.18%

TABLE 4 Panel S + S Sensitivity Specificity hsa-miR-3621 + hsa-miR-2051.71 82.46%   88% hsa-miR-3621 + hsa-miR-3607-5p 1.71 82.46% 88.24%hsa-miR-3621 + hsa-miR-665 1.68 82.46% 85.29% hsa-miR-665 + hsa-miR-2051.67 75.44% 91.18% hsa-miR-3621 + hsa-miR-1469 1.63 68.42% 94.12%hsa-miR-3621 + hsa-miR-33b* 1.61 78.95% 82.35% hsa-miR-3621 +hsa-miR-1181 1.61 78.95% 82.35% hsa-miR-3621 + hsa-miR-182* 1.61 96.49%  65% hsa-miR-183 + hsa-miR-205 1.60 89.47% 70.59% hsa-miR-3621 +hsa-miR-602 1.57 80.70% 76.47%

TABLE 5 Panel S + S Sensitivity Specificity hsa-miR-3621 +hsa-miR-1469 + 1.78 80.70% 97.06% hsa-miR-205 hsa-miR-3621 +hsa-miR-665 + 1.76 78.95% 97.06% hsa-miR-1469 hsa-miR-183 +hsa-miR-1469 + 1.75 84.21% 91.18% hsa-miR-205 hsa-miR-3621 +hsa-miR-205 + 1.75 80.70% 94.12% hsa-miR-1181 hsa-miR-3621 +hsa-miR-183 + 1.73 87.72% 85.29% hsa-miR-205 hsa-miR-3621 +hsa-miR-1181 + 1.72 84.21% 88.24% hsa-miR-3607-5p hsa-miR-3621 +hsa-miR-602 + 1.72 80.70% 91.18% hsa-miR-205 hsa-miR-3621 +hsa-miR-33b* + 1.72 80.70% 91.18% hsa-miR-205 hsa-miR-3621 +hsa-miR-602 + 1.71 85.96% 85.29% hsa-miR-3607-5p hsa-miR-3621 +hsa-miR-1469 + 1.71 82.46% 88.24% hsa-miR-3607-5p

TABLE 6 Panel S + S Sensitivity Specificity hsa-miR-3621 + hsa-miR-183 +1.80 85.96% 94.12% hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 +hsa-miR-183 + 1.78 84.21% 94.12% hsa-miR-205 + hsa-miR-3607-5phsa-miR-183 + hsa-miR-33b* + 1.78 84.21%   94% hsa-miR-1469 +hsa-miR-205 hsa-miR-183 + hsa-miR-1469 + 1.78 84.21% 94.12%hsa-miR-205 + hsa-miR-3607-5p hsa-miR-183 + hsa-miR-665 + 1.77 85.96%91.18% hsa-miR-1469 + hsa-miR-205 hsa-miR-183 + hsa-miR-602 + 1.7785.96% 91.18% hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 + hsa-miR-663 +1.76 78.95% 97.06% hsa-miR-33b* + hsa-miR-205 hsa-miR-3621 +hsa-miR-602 + 1.76 78.95% 97.06% hsa-miR-205 + hsa-miR-3607-5phsa-miR-3621 + hsa-miR-33b* + 1.76 78.95% 97.06% hsa-miR-205 +hsa-miR-1181 hsa-miR-183 + hsa-miR-663 + 1.75 84.21% 91.18%hsa-miR-1469 + hsa-miR-205

TABLE 7 Panel S + S Sensitivity Specificity hsa-miR-183 + hsa-miR-665 +hsa-miR- 1.83 85.96% 97.06% 1469 + hsa-miR-205 + hsa-miR-3607-5phsa-miR-183 + hsa-miR-182* + hsa-miR- 1.81 84.21% 97.06% 1469 +hsa-miR-205 + hsa-miR-3607-5p hsa-miR-3621 + hsa-miR-183 + hsa-miR- 1.8085.96% 94.12% 665 + hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 +hsa-miR-183 + hsa-miR- 1.80 85.96% 94.12% 663 + hsa-miR-1469 +hsa-miR-205 hsa-miR-3621 + hsa-miR-183 + hsa-miR- 1.80 85.96% 94.12%1291 + hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 + hsa-miR-183 + hsa-miR-1.80 85.96% 94.12% 602 + hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 +hsa-miR-183 + hsa-miR- 1.80 85.96% 94.12% 182* + hsa-miR-1469 +hsa-miR-205 hsa-miR-3621 + hsa-miR-183 + hsa-miR- 1.80 85.96% 94.12%33b* + hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 + hsa-miR-183 + hsa-miR-1.80 85.96% 94.12% 1469 + hsa-miR-205 + hsa-miR-1181 hsa-miR-183 +hsa-miR-665 + hsa-miR- 1.80 85.96% 94.12% 602 + hsa-miR-1469 +hsa-miR-205

TABLE 8 Panel S + S Sensitivity Specificity hsa-miR-183 + hsa-miR-665 +hsa-miR- 1.83 85.96% 97.06% 663 + hsa-miR-1469 + hsa-miR- 205 +hsa-miR-3607-5p hsa-miR-183 + hsa-miR-665 + hsa-miR- 1.83 85.96% 97.06%182* + hsa-miR-1469 + hsa-miR- 205 + hsa-miR-3607-5p hsa-miR-665 +hsa-miR-182 + hsa-miR- 1.82 87.72% 94.12% 1291 + hsa-miR-1469 + hsa-miR-205 + hsa-miR-3607-5p hsa-miR-3621 + hsa-miR-182 + hsa-miR- 1.81 84.21%97.06% 494 + hsa-miR-1973 + hsa-miR- 1469 + hsa-miR-205 hsa-miR-183 +hsa-miR-665 + hsa-miR- 1.81 84.21%   97% 1291 + hsa-miR-1469 + hsa-miR-205 + hsa-miR-3607-5p hsa-miR-183 + hsa-miR-663 + hsa-miR- 1.81 84.21%97.06% 1291 + hsa-miR-33b* + hsa-miR- 205 + hsa-miR-3607-5phsa-miR-183 + hsa-miR-663 + hsa-miR- 1.81 84.21% 97.06% 182* +hsa-miR-1469 + hsa-miR- 205 + hsa-miR-3607-5p hsa-miR-183 +hsa-miR-182* + hsa-miR- 1.81 84.21% 97.06% 33b* + hsa-miR-1469 +hsa-miR- 205 + hsa-miR-3607-5p hsa-miR-183 + hsa-miR-182* + hsa-miR-1.81 84.21% 97.06% 1973 + hsa-miR-1469 + hsa-miR- 205 + hsa-miR-3607-5phsa-miR-182 + hsa-miR-1291 + hsa-miR- 1.81 84.21% 97.06% 1973 +hsa-miR-1469 + hsa-miR- 205 + hsa-miR-3607-5p

TABLE 9 Panel S + S Sensitivity Specificity hsa-miR-3621 + hsa-miR-183 +hsa- 1.83 85.96% 97.06% miR-665 + hsa-miR-663 + hsa-miR- 182 +hsa-miR-1469 + hsa-miR-205 hsa-miR-3621 + hsa-miR-183 + hsa- 1.83 85.96%97.06% miR-663 + hsa-miR-182 + hsa-miR- 602 + hsa-miR-1469 + hsa-miR-205hsa-miR-3621 + hsa-miR-1291 + hsa- 1.83 85.96% 97.06% miR-602 +hsa-miR-1973 + hsa-miR- 1469 + hsa-miR-205 + hsa-miR-1181 hsa-miR-183 +hsa-miR-665 + hsa-miR- 1.83 85.96% 97.06% 663 + hsa-miR-1291 + hsa-miR-1469 + hsa-miR-205 + hsa-miR-3607-5p hsa-miR-183 + hsa-miR-665 +hsa-miR- 1.83 85.96% 97.06% 663 + hsa-miR-182* + hsa-miR- 1469 +hsa-miR-205 + hsa-miR-3607-5p hsa-miR-183 + hsa-miR-665 + hsa-miR- 1.8385.96% 97.06% 182 + hsa-miR-1291 + hsa-miR- 1469 + hsa-miR-205 +hsa-miR-3607-5p hsa-miR-183 + hsa-miR-182 + hsa-miR- 1.83 85.96% 97.06%1291 + hsa-miR-182* + hsa-miR- 1469 + hsa-miR-205 + hsa-miR-3607-5phsa-miR-663 + hsa-miR-182 + hsa-miR- 1.83 85.96% 97.06% 1291 +hsa-miR-1973 + hsa-miR- 1469 + hsa-miR-205 + hsa-miR-3607-5phsa-miR-182 + hsa-miR-1291 + hsa- 1.83 85.96% 97.06% miR-33b* +hsa-miR-1973 + hsa-miR- 1469 + hsa-miR-205 + hsa-miR-3607-5phsa-miR-182 + hsa-miR-1291 + hsa- 1.83 85.96% 97.06% miR-1973 +hsa-miR-1469 + hsa-miR- 205 + hsa-miR-1181 + hsa-miR-3607-5p

Panel Data (Tables 10 to 16): Aggressive Vs Indolent

Table 10-16 list biomarkers or panels of biomarkers useful with theinvention, for comparing samples from aggressive PC “case” and indolentPC “control”. The measured biomarker(s) can be (i) up-regulated (anincrease in fold-change, when compared to control samples) or (ii)down-regulated (a decrease in fold-change, when compared to controlsamples).

Columns (Tables 10 to 16)

-   -   (i) The symbol for the relevant biomarker (or, for Tables 11-16,        biomarkers in the panel).    -   (ii) S+S is the sum of the sensitivity and specificity columns.        These final two columns show the sensitivity and specificity of        a test based solely on the relevant biomarker (or, for Tables        11-16, panel) shown in the left-hand column when applied to the        samples used in the examples.

TABLE 10 Biomarker^((i)) S + S^((ii)) Sensitivity Specificityhsa-miR-99b* 1.24 82.35% 41.18% hsa-miR-210 1.14 64.71% 49.02%hsa-miR-200b 1.12 70.59% 41.18% hsa-miR-183 1.06 88.24% 17.65%hsa-miR-92b 1.06 88.24% 17.65% hsa-miR-183* 1.06 94.12% 11.76%hsa-miR-449a 1.02 94.12% 7.84% hsa-miR-133b 0.96 94.12% 1.96%hsa-miR-182* 0.96 94.12% 1.96% hsa-miR-139 0.96 94.12% 1.96%

TABLE 11 Panel S + S Sensitivity Specificity hsa-miR-99b* + hsa-miR-200b1.41 94.12% 47.06% hsa-miR-210 + hsa-miR-99b* 1.35   94% 41.18%hsa-miR-183 + hsa-miR-99b* 1.31 94.12% 37.25% hsa-miR-99b* +hsa-miR-183* 1.31 94.12% 37.25% hsa-miR-182* + hsa-miR-99b* 1.29 94.12%35.29% hsa-miR-99b* + hsa-miR-139 1.29 94.12% 35.29% hsa-miR-99b* +hsa-miR-96 1.29 88.24% 41.18% hsa-miR-99b* + hsa-miR-582-3p 1.29 88.24%41.18% hsa-miR-99b* + hsa-miR-1 1.27 94.12% 33.33% hsa-miR-99b* +hsa-miR-429 1.27 94.12% 33.33%

TABLE 12 Panel S + S Sensitivity Specificity hsa-miR-182* +hsa-miR-99b* + hsa- 1.41 94.12% 47.06% miR-200b hsa-miR-99b* +hsa-miR-429 + hsa- 1.41 94.12% 47.06% miR-96 hsa-miR-210 +hsa-miR-99b* + hsa- 1.39 82.35% 56.86% miR-96 hsa-miR-99b* +hsa-miR-582-3p + hsa- 1.39 94.12% 45.10% miR-200b hsa-miR-210 +hsa-miR-99b* + hsa-miR- 1.37 94.12% 43.14% 582-3p hsa-miR-182* +hsa-miR-99b* + hsa- 1.37 94.12% 43.14% miR-183* hsa-miR-183 +hsa-miR-99b* + hsa- 1.37 94.12% 43.14% miR-200b hsa-miR-183 +hsa-miR-139 + hsa- 1.37 76.47% 60.78% miR-96 hsa-miR-99b* + hsa-miR-96 +hsa- 1.37 82.35% 54.90% miR-200b hsa-miR-99b* + hsa-miR-92b + hsa- 1.3794.12% 43.14% miR-200b

TABLE 13 Panel S + S Sensitivity Specificity hsa-miR-210 +hsa-miR-99b* + hsa-miR- 1.53 88.24% 64.71% 429 + hsa-miR-96hsa-miR-210 + hsa-miR-99b* + hsa-miR- 1.53 88.24% 64.71% 139 +hsa-miR-96 hsa-miR-210 + hsa-miR-99b* + hsa- 1.51 76.47% 74.51% miR-96 +hsa-miR-200b hsa-miR-449a + hsa-miR-99b* + hsa- 1.49 88.24% 60.78%miR-96 + hsa-miR-200b hsa-miR-133a + hsa-miR-210 + hsa-miR- 1.49 94.12%54.90% 99b* + hsa-miR-96 hsa-miR-133b + hsa-miR-210 + hsa-miR- 1.4994.12% 54.90% 99b* + hsa-miR-96 hsa-miR-210 + hsa-miR-99b* + hsa-miR-1.49 88.24% 60.78% 96 + hsa-miR-188-3p hsa-miR-182* + hsa-miR-99b* +hsa- 1.49 94.12% 54.90% miR-429 + hsa-miR-96 hsa-miR-99b* + hsa-miR-96 +hsa-miR- 1.49 82.35% 66.67% 188-3p + hsa-miR-200b hsa-miR-210 +hsa-miR-182* + hsa-miR- 1.47 70.59% 76.47% 139 + hsa-miR-96

TABLE 14 Panel S + S Sensitivity Specificity hsa-miR-449a +hsa-miR-99b* + hsa- 1.63 94.12% 68.63% miR-96 + hsa-miR-188-3p + hsa-miR-200b hsa-miR-133a + hsa-miR-210 + hsa-miR- 1.59 88.24% 70.59% 99b* +hsa-miR-96 + hsa-miR-200b hsa-miR-210 + hsa-miR-378 + hsa-miR- 1.5994.12% 64.71% 99b* + hsa-miR-96 + hsa-miR-200b hsa-miR-210 +hsa-miR-99b* + hsa- 1.59 94.12% 64.71% miR-1 + hsa-miR-429 + hsa-miR-96hsa-miR-210 + hsa-miR-99b* + hsa- 1.59 82.35% 76.47% miR-1 +hsa-miR-96 + hsa-miR-200b hsa-miR-210 + hsa-miR-99b* + hsa-miR- 1.5970.59% 88.24% 139 + hsa-miR-96 + hsa-miR-183* hsa-miR-210 +hsa-miR-378 + hsa-miR- 1.57 88.24% 68.63% 99b* + hsa-miR-96 +hsa-miR-183* hsa-miR-210 + hsa-miR-183 + hsa-miR- 1.57 70.59% 86.27%139 + hsa-miR-96 + hsa-miR-188-3p hsa-miR-99b* + hsa-miR-1 + hsa- 1.5794.12% 62.75% miR-429 + hsa-miR-96 + hsa-miR-183* hsa-miR-449a +hsa-miR-99b* + hsa- 1.55 88.24% 66.67% miR-1 + hsa-miR-96 + hsa-miR-200b

TABLE 15 Sensi- Spe- Panel S + S tivity cificity hsa-miR-210 +hsa-miR-378 + hsa-miR- 1.69 88.24% 80.39% 99b* + hsa-miR-139 +hsa-miR-96 + hsa-miR- 183* hsa-miR-449a + hsa-miR-183 + hsa-miR- 1.6794.12% 72.55% 99b* + hsa-miR-96 + hsa-miR-188-3p + hsa- miR-200bhsa-miR-133b + hsa-miR-210 + hsa-miR- 1.67 88.24% 78.43% 99b* +hsa-miR-96 + hsa-miR-188-3p + hsa- miR-200b hsa-miR-210 + hsa-miR-378 +hsa-miR- 1.67 94.12% 72.55% 99b* + hsa-miR-429 + hsa-miR-96 + hsa-miR-183* hsa-miR-449a + hsa-miR-133b + hsa-miR- 1.65 88.24% 76.47% 210 +hsa-miR-99b* + hsa-miR-96 + hsa-miR- 200b hsa-miR-449a + hsa-miR-210 +hsa-miR- 1.65 94.12% 70.59% 378 + hsa-miR-99b* + hsa-miR-96 + hsa-miR-200b hsa-miR-449a + hsa-miR-183 + hsa-miR- 1.65 94.12% 70.59% 99b* +hsa-miR-429 + hsa-miR-96 + hsa-miR- 188-3p hsa-miR-449a + hsa-miR-99b* +hsa-miR- 1.65   94% 70.59% 1 + hsa-miR-96 + hsa-miR-188-3p + hsa-miR-200b hsa-miR-133a + hsa-miR-210 + hsa-miR- 1.65   88% 76.47% 99b* +hsa-miR-96 + hsa-miR-188-3p + hsa- miR-200b hsa-miR-133b + hsa-miR-210 +hsa-miR- 1.65 88.24% 76.47% 99b* + hsa-miR-139 + hsa-miR-96 + hsa-miR-200b

TABLE 16 Sensi- Spe- Panel S + S tivity cificity hsa-miR-133a +hsa-miR-210 + hsa-miR- 1.71 88.24% 82.35% 99b* + hsa-miR-139 +hsa-miR-96 + hsa-miR- 188-3p + hsa-miR-200b hsa-miR-133b + hsa-miR-210 +hsa-miR- 1.71 88.24% 82.35% 99b* + hsa-miR-139 + hsa-miR-96 + hsa-miR-188-3p + hsa-miR-200b hsa-miR-210 + hsa-miR-378 + hsa-miR- 1.71 94.12%76.47% 99b* + hsa-miR-139 + hsa-miR-96 + hsa-miR- 200b + hsa-miR-183*hsa-miR-449a + hsa-miR-133a + hsa-miR- 1.69 88.24% 80.39% 210 +hsa-miR-99b* + hsa-miR-96 + hsa-miR- 188-3p + hsa-miR-200bhsa-miR-449a + hsa-miR-210 + hsa-miR- 1.69 88.24% 80.39% 183 +hsa-miR-99b* + hsa-miR-429 + hsa- miR-188-3p + hsa-miR-200bhsa-miR-449a + hsa-miR-182* + hsa-miR- 1.69 94.12% 74.51% 183 +hsa-miR-99b* + hsa-miR-96 + hsa- miR-188-3p + hsa-miR-200bhsa-miR-133a + hsa-miR-210 + hsa-miR- 1.69 88.24% 80.39% 99b* +hsa-miR-429 + hsa-miR-96 + hsa-miR- 188-3p + hsa-miR-200b hsa-miR-210 +hsa-miR-378 + hsa-miR- 1.69 88.24% 80.39% 182* + hsa-miR-99b* +hsa-miR-139 + hsa- miR-96 + hsa-miR-200b hsa-miR-210 + hsa-miR-378 +hsa-miR- 1.69 88.24% 80.39% 99b* + hsa-miR-1 + hsa-miR-139 + hsa-miR-96 + hsa-miR-183* hsa-miR-210 + hsa-miR-378 + hsa-miR- 1.69 88.24%80.39% 99b* + hsa-miR-139 + hsa-miR-96 + hsa-miR- 188-3p + hsa-miR-200b

TABLE 17 No.^((i)) Symbol^((ii)) Name^((iii)) GI^((iv)) ID^((v)) 1MIR3621 microRNA 3621 312147424 100500811 3 MIR221 microRNA 221262206342 407006 4 MIR183 microRNA 183 262206247 406959 6 MIR375microRNA 375 262206227 494324 7 MIR665 microRNA 665 262206150 1001263158 MIR96 microRNA 96 262205747 407053 10 MIR663A microRNA 663a 262206270724033 11 MIR182 microRNA 182 262206242 406958 13 MIR494 microRNA 494262205218 574452 14 MIR148A microRNA 148a 262206160 406940 16 MIR1291microRNA 1291 269847156 100302221 17 MIR602 microRNA 602 262206006693187 12 MIR182 microRNA 182 262206242 406958 19 MIR33B microRNA 33b262206145 693120 20 MIR1973 microRNA 1973 269847660 100302290 21MIR153-1/ microRNA 153-1/ 262205338/ 406944/ MIR153-2 microRNA 153-2262205343 406945 22 MIR141 microRNA 141 262205311 406933 24 MIR1469microRNA 1469 269847566 100302258 25 MIR205 microRNA 205 262206281406988 27 MIR1181 microRNA 1181 269847026 100302213 28 MIR3607 microRNA3607 312147410 100500805 30 MIR449A microRNA 449a 262205416 554213 31MIR133A1/ microRNA 133a-1/ 262205283/ 406922/ MIR133A2 microRNA 133a-2262205288 406923 32 MIR133B microRNA 133b 262205134 442890 33 MIR210microRNA 210 262206286 406992 35 MIR378A microRNA 378a 262206243 49432737 MIR99B microRNA 99b 262206116 407056 38 MIR1-1/ microRNA 1-1/262205804/ 406904/ MIR1-2 microRNA 1-2 262205216 406905 39 MIR429microRNA 429 262205400 554210 41 MIR139 microRNA 139 262206187 406931 43MIR188 microRNA 188 262205439 406964 45 MIR92B microRNA 92b 262205754693235 47 MIR582 microRNA 582 262205881 693167 49 MIR200B microRNA 200b262206358 406984 5 MIR183 microRNA 183 262206247 406959

Table 17 lists all the biomarkers useful with the invention (from Table1 and Table 2). Table 17 states the official name of the miRNAbiomarkers (according to NCBI), as well as their unique GenInfoIdentifier number and Entrez GeneID number.

Columns

(i) This number is the SEQ ID NO: for the sequence of the mature,expressed miRNA biomarker, as shown in the sequence listing.

(ii) The “Symbol” column is as described for Table 1.

(iii) This name is taken from the Official Full Name provided byNational Center for Biotechnology Information (NCBI). A miRNA antigenmay have been referred to by one or more pseudonyms in the prior art.The invention relates to these miRNA regardless of their nomenclature.

(iv) A “GI” number, “GenInfo Identifier”, is a series of digits assignedconsecutively to each sequence record processed by NCBI when sequencesare added to its databases. The GI number bears no resemblance to theaccession number of the sequence record. When a sequence is updated(e.g. for correction, or to add more annotation or information) itreceives a new GI number. Thus the sequence associated with a given GInumber is never changed.

(v) The “ID” column shows the Entrez GeneID number for the miRNA. AnEntrez GeneID value is unique across all taxa.

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TABLE 18 SEQ Mature Mature SEQ Mature Mature SEQ miRNA Hairpin HairpinID accession sequence ID accession sequence ID Chromosomal name^((i))accession^((ii)) sequence^((iii)) NO (-5p)^((iv)) (-5p)^((v)) NO(-3p)^((vi)) (-3p)^((vii)) NO location^((viii)) hsa- MI0016012GUGAGCUGCUGGGGA 50 MIMAT00 CGCGGGUC 1 chr9:1391834 miR- CGCGGGUCGGGGUCU18002 GGGGUCUG 59-139183543 3621 GCAGGGCGGUGCGGC CAGG AGCCGCCACCUGACGCCGCGCCUUUGUCUG UGUCCCACAG hsa- MI0000298 UGAACAUCCAGGUCU 51 MIMAT00ACCUGGCA 2 MIMAT00 AGCUACAU 3 chrX:4549052 miR- GGGGCAUGAACCUGG 04568UACAAUGU 00278 UGUCUGCU 9-45490638 221 CAUACAAUGUAGAUU AGAUUU GGGUUUCUCUGUGUUCGUUAGG CAACAGCUACAUUGU CUGCUGGGUUUCAGG CUACCUGGAAACAUG UUCUChsa- MI0000273 CCGCAGAGUGUGACU 52 MIMAT00 UAUGGCAC 4 MIMAT00 GUGAAUUA 5chr7:1292019 miR- CCUGUUCUGUGUAUG 00261 UGGUAGAA 04560 CCGAAGGG81-129202090 183 GCACUGGUAGAAUUC UUCACU CCAUAA ACUGUGAACAGUCUCAGUCAGUGAAUUACC GAAGGGCCAUAAACA GAGCAGAGACAGAUC CACGA hsa- MI0000783CCCCGCGACGAGCCC 53 MIMAT00 UUUGUUCG 6 chr2:2195746 miR- CUCGCACAAACCGGA00728 UUCGGCUC 11-219574674 375 CCUGAGCGUUUUGUU GCGUGA CGUUCGGCUCGCGUGAGGC hsa- MI0005563 UCUCCUCGAGGGGUC 54 MIMAT00 ACCAGGAG 7 chr14:100411miR- UCUGCCUCUACCCAG 04952 GCUGAGGC 123- 665 GACUCUUUCAUGACC CCCU100411194 AGGAGGCUGAGGCCC CUCACAGGCGGC hsa- MI0000098 UGGCCGAUUUUGGCA 55MIMAT00 UUUGGCAC 8 MIMAT00 AAUCAUGU 9 chr7:1292017 miR-96CUAGCACAUUUUUGC 00095 UAGCACAU 04510 GCAGUGCC 68-129201845UUGUGUCUCUCCGCU UUUUGCU AAUAUG CUGAGCAAUCAUGUG CAGUGCCAAUAUGGG AAA hsa-MI0003672 CCUUCCGGCGUCCCA 56 MIMAT00 AGGCGGGG 10 chr20:261368 miR-GGCGGGGCGCCGCGG 03326 CGCCGCGG 22-26136914 663a GACCGCCCUCGUGUC GACCGCUGUGGCGGUGGGAUC CCGCGGCCGUGUUUU CCUGGUGGCCCGGCC AUG hsa- MI0000272GAGCUGCUUGCCUCC 57 MIMAT00 UUUGGCAA 11 MIMAT00 UGGUUCUA 12 chr7:1291974miR- CCCCGUUUUUGGCAA 00259 UGGUAGAA 00260 GACUUGCC 59-129197568 182UGGUAGAACUCACAC CUCACACU AACUA UGGUGAGGUAACAGG  AUCCGGUGGUUCUAGACUUGCCAACUAUGG GGCGAGGACUCAGCC GGCAC hsa- MI0003134 GAUACUCGAAGGAGA 58MIMAT00 UGAAACAU 13 chr14:100565 miR- GGUUGUCCGUGUUGU 02816 ACACGGGA724- 494 CUUCUCUUUAUUUAU AACCUC 100565804 GAUGAAACAUACACGGGAAACCUCUUUUUU AGUAUC hsa- MI0000253 GAGGCAAAGUUCUGA 59 MIMAT00AAAGUUCU 14 MIMAT00 UCAGUGCA 15 chr7:2595606 miR- GACACUCCGACUCUG 04549GAGACACU 00243 CUACAGAA 4-25956131 148a AGUAUGAUAGAAGUC CCGACU CUUUGUAGUGCACUACAGAAC UUUGUCUC hsa- MI0006353 GGUAGAAUUCCAGUG 60 MIMAT00UGGCCCUG 16 chr12:473344 miR- GCCCUGACUGAAGAC 05881 ACUGAAGA 94-473345801291 CAGCAGUUGUACUGU CCAGCAGU GGCUGUUGGUUUCAA GCAGAGGCCUAAAGGACUGUCUUCCUG hsa- MI0003615 UUCUCACCCCCGCCU 61 MIMAT00 GACACGGG 17chr9:1398526 miR- GACACGGGCGACAGC 03270 CGACAGCU 92-139852789 602UGCGGCCCGCUGUGU GCGGCCC UCACUCGGGCCGAGU GCGUCUCCUGUCAGG CAAGGGAGAGCAGAGCCCCCCUG hsa- MI0000272 GAGCUGCUUGCCUCC 57 MIMAT00 UUUGGCAA 11 MIMAT00UGGUUCUA 12 chr7:1291974 miR- CCCCGUUUUUGGCAA 00259 UGGUAGAA 00260GACUUGCC 59-129197568 182* UGGUAGAACUCACAC CUCACACU AACUAUGGUGAGGUAACAGG AUCCGGUGGUUCUAG ACUUGCCAACUAUGG GGCGAGGACUCAGCC GGCAChsa- MI0003646 GCGGGCGGCCCCGCG 62 MIMAT00 GUGCAUUG 18 MIMAT00 CAGUGCCU19 chr17:176578 miR- GUGCAUUGCUGUUGC 03301 CUGUUGCA 04811 CGGCAGUG75-17657970 33b* AUUGCACGUGUGUGA UUGC CAGCCC GGCGGGUGCAGUGCCUCGGCAGUGCAGCCC GGAGCCGGCCCCUGG CACCAC hsa- MI0009983 UAUGUUCAACGGCCA 63MIMAT00 ACCGUGCA 20 chr4:1174403 miR- UGGUAUCCUGACCGU 09448 AAGGUAGC30-117440373 1973 GCAAAGGUAGCAUA AUA hsa- MI0000463 CUCACAGCUGCCAGU 64MIMAT00 UUGCAUAG 21 chr2:2198670 miR- GUCAUUUUUGUGAUC 00439 UCACAAAA77-219867166 153-1 UGCAGCUAGUAUUCU GUGAUC CACUCCAGUUGCAUAGUCACAAAAGUGAUC AUUGGCAGGUGUGGC hsa- MI0000464 AGCGGUGGCCAGUGU 65MIMAT00 UUGCAUAG 21 chr7:1570597 miR- CAUUUUUGUGAUGUU 00439 UCACAAAA89-157059875 153-2 GCAGCUAGUAAUAUG GUGAUC AGCCCAGUUGCAUAGUCACAAAAGUGAUCA UUGGAAACUGUG hsa- MI0000457 CGGCCGGCCCUGGGU 66 MIMAT00CAUCUUCC 22 MIMAT00 UAACACUG 23 chr12:694352 miR- CCAUCUUCCAGUACA 04598AGUACAGU 00432 UCUGGUAA 1-6943615 141* GUGUUGGAUGGUCUA  GUUGGA AGAUGGAUUGUGAAGCUCCUA ACACUGUCUGGUAAA GAUGGCUCCCGGGUG GGUUC hsa- MI0007074CUCGGCGCGGGGCGC 67 MIMAT00 CUCGGCGC 24 chr15:946774 miR- GGGCUCCGGGUUGGG07347 GGGGCGCG 94-94677540 1469 GCGAGCCAACGCCGG GGCUCC GG hsa- MI0000285AAAGAUCCUCAGACA 68 MIMAT00 UCCUUCAU 25 MIMAT00 GAUUUCAG 26 chr1:2076721miR- AUCCAUGUGCUUCUC 00266 UCCACCGG 09197 UGGAGUGA 01-207672210 205UUGUCCUUCAUUCCA AGUCUG AGUUC CCGGAGUCUGUCUCA UACCCAACCAGAUUUCAGUGGAGUGAAGUU CAGGAGGCAUGGAGC UGACA hsa- MI0006274 UCCACUGCUGCCGCC 69MIMAT00 CCGUCGCC 27 chr19:103751 miR- GUCGCCGCCACCCGA 05826 GCCACCCG34-10375214 1181 GCCGGAGCGGGCUGG  AGCCG GCCGCCAAGGCAAGA UGGUGGACUACAGCGUGUGGG hsa- MI0015997 AAGGUUGCGGUGCAU 70 MIMAT00 GCAUGUGA 28 MIMAT00ACUGUAAA 29 chr5:8595207 miR- GUGAUGAAGCAAAUC 17984 UGAAGCAA 17985CGCUUUCU 0-85952148 3607 AGUAUGAAUGAAUUC AUCAGU GAUG AUGAUACUGUAAACGCUUUCUGAUGUACUA CUCA hsa- MI0001648 CUGUGUGUGAUGAGC 71 MIMAT00 UGGCAGUG30 chr5:5450211 miR- UGGCAGUGUAUUGUU 01541 UAUUGUUA 7-54502207 449aAGCUGGUUGAAUAUG GCUGGU UGAAUGGCAUCGGCU AACAUGCAACUGCUG UCUUAUUGCAUAUAC Ahsa- MI0000450 ACAAUGCUUUGCUAG 72 MIMAT00 UUUGGUCC 31 chr18:176596 miR-AGCUGGUAAAAUGGA 00427 CCUUCAAC 57-17659744 133a-1 ACCAAAUCGCCUCUU CAGCUGCAAUGGAUUUGGUCC CCUUCAACCAGCUGU AGCUAUGCAUUGA hsa- MI0000451GGGAGCCAAAUGCUU 73 MIMAT00 UUUGGUCC 31 chr20:605725 miR- UGCUAGAGCUGGUAA00427 CCUUCAAC 64-60572665 133a-2 AAUGGAACCAAAUCG CAGCUG ACUGUCCAAUGGAUUUGGUCCCCUUCAACC AGCUGUAGCUGUGCA UUGAUGGCGCCG hsa- MI0000822CCUCAGAAGAAAGAU 74 MIMAT00 UUUGGUCC 32 chr6:5212168 miR- GCCCCCUGCUCUGGC00770 CCUUCAAC 0-52121798 133b UGGUCAAACGGAACC CAGCUA AAGUCCGUCUUCCUGAGAGGUUUGGUCCCC UUCAACCAGCUACAG CAGGGCUGGCAAUGC CCAGUCCUUGGAGA hsa-MI0000286 ACCCGGCAGUGCCUC 75 MIMAT00 CUGUGCGU 33 chr11:558089- miR-CAGGCGCAGGGCAGC 00267 GUGACAGC 558198 210 CCCUGCCCACCGCAC GGCUGAACUGCGCUGCCCCAG  ACCCACUGUGCGUGU GACAGCGGCUGAUCU GUGCCUGGGCAGCGC GACCChsa- MI0000786 AGGGCUCCUGACUCC 76 MIMAT00 CUCCUGAC 34 MIMAT00 ACUGGACU35 chr5:1490925 miR- AGGUCCUGUGUGUUA 00731 UCCAGGUC 00732 UGGAGUCA81-149092646 378a CCUAGAAAUAGCACU CUGUGU GAAGG GGACUUGGAGUCAGA AGGCCUhsa- MI0000746 GGCACCCACCCGUAG 77 MIMAT00 CACCCGUA 36 MIMAT00 CAAGCUCG37 chr19:568876 miR- AACCGACCUUGCGGG 00689 GAACCGAC 04678 UGUCUGUG77-56887746 99b* GCCUUCGCCGCACAC CUUGCG GGUCCG AAGCUCGUGUCUGUGGGUCCGUGUC hsa- MI0000651 UGGGAAACAUACUUC 78 MIMAT00 UGGAAUGU 38chr20:605619 miR-1-1 UUUAUAUGCCCAUAU 00416 AAAGAAGU 58-60562028GGACCUGCUAAGCUA AUGUAU UGGAAUGUAAAGAAG UAUGUAUCUCA hsa- MI0000437ACCUACUCAGAGUAC 79 MIMAT00 UGGAAUGU 38 chr18:176629 miR-1-2AUACUUCUUUAUGUA 00416 AAAGAAGU 63-17663047 CCCAUAUGAACAUAC AUGUAUAAUGCUAUGGAAUGU AAAGAAGUAUGUAUU UUUGGUAGGC hsa- MI0001641CGCCGGCCGAUGGGC 80 MIMAT00 UAAUACUG 39 chr1:1094248- miR-GUCUUACCAGACAUG 01536 UCUGGUAA 1094330 429 GUUAGACCUGGCCCU AACCGUCUGUCUAAUACUGUC UGGUAAAACCGUCCA UCCGCUGC hsa- MI0000261 GUGUAUUCUACAGUG81 MIMAT00 UCUACAGU 40 MIMAT00 GGAGACGC 41 chr11:720037 miR-CACGUGUCUCCAGUG 00250 GCACGUGU 04552 GGCCCUGU 55-72003822 139UGGCUCGGAGGCUGG CUCCAG UGGAGU AGACGCGGCCCUGUU GGAGUAAC hsa- MI0000484UGCUCCCUCUCUCAC 82 MIMAT00 CAUCCCUU 42 MIMAT00 CUCCCACA 43 chrX:4965484miR- AUCCCUUGCAUGGUG 00457 GCAUGGUG 04613 UGCAGGGU 9-49654934 188GAGGGUGAGCUUUCU GAGGG UUGCA GAAAACCCCUCCCAC AUGCAGGGUUUGCAG GAUGGCGAGCChsa- MI0003560 CGGGCCCCGGGCGGG 83 MIMAT00 AGGGACGG 44 MIMAT00 UAUUGCAC45 chr1:1534315 miR- CGGGAGGGACGGGAC 04792 GACGCGGU 03218 UCGUCCCG92-153431687 92b GCGGUGCAGUGUUGU GCAGUG GCCUCC UUUUUCCCCCGCCAAUAUUGCACUCGUCCC GGCCUCCGGCCCCCC CGGCCC hsa- MI0003589 AUCUGUGCUCUUUGA 84MIMAT00 UUACAGUU 46 MIMAT00 UAACUGGU 47 chr5:5903518 miR-UUACAGUUGUUCAAC 03247 GUUCAACC 04797 UGAACAAC 9-59035286 582CAGUUACUAAUCUAA AGUUACU UGAACC CUAAUUGUAACUGGU UGAACAACUGAACCCAAAGGGUGCAAAGUA GAAACAUU hsa- MI0000342 CCAGCUCGGGCAGCC 85 MIMAT00CAUCUUAC 48 MIMAT00 UAAUACUG 49 chr1:1092347- miR- GUGGCCAUCUUACUG 04571UGGGCAGC 00318 CCUGGUAA 1092441 200b GGCAGCAUUGGAUGG AUUGGA UGAUGAAGUCAGGUCUCUAAU ACUGCCUGGUAAUGA UGACGGCGGAGCCCU GCACG hsa- MI0000273CCGCAGAGUGUGACU 52 MIMAT00 UAUGGCAC 4 MIMAT00 GUGAAUUA 5 chr7:1292019miR- CCUGUUCUGUGUAUG 00261 UGGUAGAA 04560 CCGAAGGG 81-129202090 183*GCACUGGUAGAAUUC UUCACU CCAUAA ACUGUGAACAGUCUC AGUCAGUGAAUUACCGAAGGGCCAUAAACA GAGCAGAGACAGAUC CACGA

Table 18 lists all the biomarkers useful with the invention (from Table1 and Table 2). Table 18 provides the accession number and sequence(according to miRBase) for the precursor hairpin, as well as the mature,processed miRNAs (for both the 5′ and 3′ arm of the hairpin, whereapplicable). Additionally, the genomic location of the hairpin is alsoprovided.

Columns

(i) The “miRNA name” column is as described above.

(ii) The “Hairpin accession” column gives the unique number of theprecursor hairpin, which is processed biologically, to yield the maturehuman miRNA, as provided by the specialist database, miRBase. The nameis correct to miRBase version 16 (released, August 2010).

(iii) The “Hairpin sequence” column gives the sequence information ofthe precursor hairpin, which is processed biologically, to yield themature human miRNA, as provided by the specialist database, miRBase. Thename is correct to miRBase version 16 (released, August 2010).

(iv) The “Mature accession (−5p)” column gives the unique number of themature, processed, miRNA located on the 5′ arm, as provided by thespecialist database, miRBase. The name is correct to miRBase version 16(released, August 2010).

(v) The “Mature sequence (−5p)” column gives the sequence information ofthe mature, processed, miRNA located on the 5′ arm, as provided by thespecialist database, miRBase. The name is correct to miRBase version 16(released, August 2010).

(vi) The “Mature accession (−3p)” column gives the unique number of themature, processed, miRNA located on the 3′ arm, as provided by thespecialist database, miRBase. The name is correct to miRBase version 16(released, August 2010).

(vii) The “Mature sequence (−3p)” column gives the sequence informationof the mature, processed, miRNA located on the 3′ arm, as provided bythe specialist database, miRBase. The name is correct to miRBase version16 (released, August 2010).

(viii) The “Chromosomal location” column gives the exact genomiclocation for the precursor hairpin, as provided by the specialistdatabase, miRBase. The name is correct to miRBase version 16 (released,August 2010).

TABLE 19 miRNA name^((i)) Assay ID^((ii)) No.^((iii)) hsa-miR-1291002838 16 hsa-miR-449a 001030 30 hsa-miR-183 002269 4 hsa-miR-1973245468_mat 20 hsa-miR-3621 463091_mat 1 hsa-miR-665 002681 7 hsa-miR-1-1002222 38 hsa-miR-133a-1 002246 31 hsa-miR-133b 002247 32

Table 19 lists the biomarkers used to assess the suitability of theclaimed diagnostic and/or prognostic markers for detecting circulatingmiRNAs within human plasma and serum.

Columns

(i) The “miRNA name” column gives the name of the human miRNA asprovided by the specialist database, miRBase, according to version 16(released, August 2010).

(ii) The “Assay ID” column gives the unique assay ID identifier used forordering the specific TaqMan miRNA assay from Life Technologies. Theassay ID is correct as of July 2013.

(iii) The SEQ ID NO: for the sequence of the mature, expressed miRNAbiomarker, as shown in Table 18

TABLE 20 Aggressive Aggressive vs indolent vs indolent CorrelatesAggressive vs Aggressive vs Indolent vs Indolent vs & normal and normalNo. Expression with tissue normal [BPH] normal [BPH] normal [BPH] normal[BPH] [BPH] log [BPH] P- miRNA name (i) (ii) (iii) data (iv) log foldchange P-value log fold change P-value fold change value hsa-miR-665 7UP Yes 1.745 9.19E−06 2.324 2.03E−09 0.002 0.996 hsa-miR-183 4 UP Yes1.026 0.016 1.107 0.004 0.196 0.553 hsa-miR-3621 1 UP Yes 1.482 0.1111.542 0.067 0.326 0.638 hsa-miR-1291 16 UP Yes 0.476 0.574 1.418 0.067−0.587 0.359 hsa-miR-133a-1 31 DOWN Yes −2.426 0.003 −0.076 0.913 −2.3691.02E−04 hsa-miR-1-1 38 DOWN Yes −1.950 0.017 0.071 0.920 −2.004 0.001hsa-miR-449a 30 UP No −1.643 0.081 0.026 0.975 −1.662 0.017 hsa-miR-197320 UP No −0.968 0.237 −0.005 0.994 −0.964 0.109 hsa-miR-133b 32 DOWN Yes−1.650 0.047 0.847 0.252 −2.284 3.77E−04

Table 20 lists the P-values and log fold changes of the miRNA markersused in the pilot prostate cancer plasma experiment, as describedherein. The categories used in the analysis are: ‘Aggressive vs normal[BPH]’; ‘Indolent vs normal [BPH]’; ‘Aggressive vs indolent and normal[BPH]’ (i.e. aggressive samples vs every other sample). The differentialexpression profile of the biomarkers used in the plasma experiment iscompared to their differential expression profile as reported in freshPC tissue.

TABLE 21 Aggressive Aggressive vs indolent vs indolent CorrelatesAggressive vs Aggressive vs Indolent vs Indolent vs & normal and normalNo. Expression with tissue normal [BPH] normal [BPH] normal [BPH] normal[BPH] [BPH] log [BPH] P- miRNA name (i) (ii) (iii) data (iv) log foldchange P-value log fold change P-value fold change value hsa-miR-3621 1UP Yes 1.47 0.011 1.85 3.30E−08 0.545 0.426 hsa-miR-665 7 UP Yes 1.4340.031 2.018 1.32E−07 0.425 0.581 hsa-miR-1973 20 UP Yes 0.978 0.192 1.290.002 0.333 0.666 hsa-miR-1291 16 UP Yes 0.237 0.808 1.326 0.012 −0.4270.662 hsa-miR-183 4 UP Yes 1.245 0.13 0.804 0.064 0.843 0.296hsa-miR-133a-1 31 DOWN No 0.428 0.504 0.464 0.171 0.196 0.756hsa-miR-133b 32 DOWN No 0.953 0.385 0.589 0.309 0.658 0.532 hsa-miR-1-138 DOWN No 0.346 0.635 0.409 0.287 0.141 0.842 hsa-miR-449a 30 UP No−1.286 0.385 0.896 0.252 −1.733 0.224

Table 21 lists the P-values and log fold changes of the miRNA markersused in the pilot prostate cancer serum experiment, as described herein.The categories used in the analysis are: ‘Aggressive vs normal [BPH]’;‘Indolent vs normal [BPH]’; ‘Aggressive vs indolent and normal [BPH]’(i.e. aggressive samples vs every other sample). The differentialexpression profile of the biomarkers used in the serum experiment iscompared to their differential expression profile as reported in freshPC tissue.

Columns (Tables 20 & 21)

(i) The “miRNA name” column gives the name of the human miRNA asprovided by the specialist database, miRBase, according to version 16(released, August 2010).

(ii) The SEQ ID NO: for the sequence of the mature, expressed miRNAbiomarker, as shown in Table 18.

(iii) The direction of expression of the miRNA marker as previouslyreported for the prostate cancer fresh PC tissue data.

(iv) Correlation of the differential expression of the claimed miRNAmarkers in prostate cancer plasma/serum vs the differential expressionof the same miRNA markers in prostate cancer fresh PC tissue.

TABLE 23 miRNA name^((i)) No.^((ii)) hsa-miR-1-1/hsa-miR-1-2 38hsa-miR-96 8 hsa-miR-141 22 hsa-miR-153-1/hsa-miR-153-2 21 hsa-miR-18211 hsa-miR-183 4 hsa-miR-375 6 hsa-miR-494 13 hsa-miR-582 47hsa-miR-1291 16 hsa-miR-1973 20 hsa-miR-3621 1hsa-miR-133a-1/hsa-miR-133a-2 31 hsa-miR-133b 32 hsa-miR-182* 12hsa-miR-183* 5 hsa-miR-33b* 19 hsa-miR-99b* 37

Table 23 lists the biomarkers used to assess the suitability of theclaimed diagnostic and/or prognostic markers for PC in formalin-fixedparaffin-embedded (FFPE) samples.

Columns

(i) The “miRNA name” column gives the name of the human miRNA asprovided by the specialist database, miRBase, according to version 16(released, August 2010).

(ii) The SEQ ID NO: for the sequence of the mature, expressed miRNAbiomarker, as shown in Table 18.

TABLE 24 Preferred Subsets hsa-miR-103, hsa-miR-1-1, hsa-miR-1181,hsa-miR-1291, hsa-miR-133a-1, hsa-miR-133b, hsa-miR- 141, hsa-miR-1469,hsa-miR-148*, hsa-miR-153, hsa-miR-182, hsa-miR-182*, hsa-miR-183,hsa-miR- 183*, hsa-miR-185, hsa-miR-191, hsa-miR-192, hsa-miR-1973,hsa-miR-200b, hsa-miR-205, hsa-miR- 210, hsa-miR-33b*, hsa-miR-3607-5p,hsa-miR-3621, hsa-miR-375, hsa-miR-378a, hsa-miR-429, hsa- miR-494,hsa-miR-582, hsa-miR-602, hsa-miR-665, hsa-miR-96, hsa-miR-99b*.hsa-miR-103, hsa-miR-1-1, hsa-miR-1181, hsa-miR-1291, hsa-miR-133a-1,hsa-miR-133b, hsa-miR- 141, hsa-miR-1469, hsa-miR-148*, hsa-miR-153,hsa-miR-182, hsa-miR-183*, hsa-miR-185, hsa-miR- 191, hsa-miR-192,hsa-miR-1973, hsa-miR-200b, hsa-miR-210, hsa-miR-33b*, hsa-miR-3607-5p,hsa- miR-3621, hsa-miR-375, hsa-miR-378a, hsa-miR-429, hsa-miR-494,hsa-miR-582, hsa-miR-602, hsa- miR-665, hsa-miR-96, hsa-miR-99b*hsa-miR-103, hsa-miR-1-1, hsa-miR-1181, hsa-miR-1291, hsa-miR-133a-1,hsa-miR-133b, hsa-miR- 141, hsa-miR-1469, hsa-miR-148*, hsa-miR-153,hsa-miR-183*, hsa-miR-185, hsa-miR-191, hsa-miR- 192, hsa-miR-1973,hsa-miR-200b, hsa-miR-210, hsa-miR-33b*, hsa-miR-3607-5p, hsa-miR-3621,hsa- miR-375, hsa-miR-378a, hsa-miR-429, hsa-miR-494, hsa-miR-582,hsa-miR-602, hsa-miR-665, hsa-miR- 96, hsa-miR-99b* hsa-miR-1181,hsa-miR-1291, hsa-miR-1469, hsa-miR-153, hsa-miR-182, hsa-miR-182*,hsa-miR-183, hsa-miR-183*, hsa-miR-1973, hsa-miR-205, hsa-miR-33b*,hsa-miR-3607-5p, hsa-miR-3621, hsa-miR- 375, hsa-miR-602 andhsa-miR-665, hsa-miR-96 hsa-miR-1181, hsa-miR-1291, hsa-miR-1469,hsa-miR-153, hsa-miR-183*, hsa-miR-1973, hsa-miR- 33b*, hsa-miR-3607-5p,hsa-miR-3621, hsa-miR-602, hsa-miR-665. hsa-miR-103, hsa-miR-1-1,hsa-miR-1291, hsa-miR-133a-1, hsa-miR-133b, hsa-miR-141, hsa-miR- 148*,hsa-miR-182, hsa-miR-183, hsa-miR-183*, hsa-miR-185, hsa-miR-191,hsa-miR-192, hsa-miR- 1973, hsa-miR-200b, hsa-miR-210, hsa-miR-3607-5p,hsa-miR-3621, hsa-miR-375, hsa-miR-378a, hsa- miR-429, hsa-miR-494,hsa-miR-582, hsa-miR-665, hsa-miR-96, hsa-miR-99b*. hsa-miR-103,hsa-miR-1-1, hsa-miR-1291, hsa-miR-133a-1, hsa-miR-133b, hsa-miR-141,hsa-miR- 148*, hsa-miR-182, hsa-miR-183*, hsa-miR-185, hsa-miR-191,hsa-miR-192, hsa-miR-1973, hsa-miR- 200b, hsa-miR-210, hsa-miR-3607-5p,hsa-miR-3621, hsa-miR-375, hsa-miR-378a, hsa-miR-429, hsa- miR-494,hsa-miR-582, hsa-miR-665, hsa-miR-96, hsa-miR-99b*. hsa-miR-103,hsa-miR-1-1, hsa-miR-1291, hsa-miR-133a-1, hsa-miR-133b, hsa-miR-141,hsa-miR- 148*, hsa-miR-182, hsa-miR-183*, hsa-miR-185, hsa-miR-191,hsa-miR-192, hsa-miR-1973, hsa-miR- 200b, hsa-miR-210, hsa-miR-3607-5p,hsa-miR-3621, hsa-miR-375, hsa-miR-378a, hsa-miR-429, hsa- miR-494,hsa-miR-582, hsa-miR-665, hsa-miR-96, hsa-miR-99b*. hsa-miR-1291,hsa-miR-133a-1, hsa-miR-133b, hsa-miR-139, hsa-miR-182, hsa-miR-182*,hsa-miR- 183, hsa-miR-183*, hsa-miR-188-3p, hsa-miR-1973, hsa-miR-200b,hsa-miR-210, hsa-miR-3621, hsa- miR-378a, hsa-miR-429, hsa-miR-449a,hsa-miR-582, hsa-miR-96, hsa-miR-99b* hsa-miR-1291, hsa-miR-133a-1,hsa-miR-133b, hsa-miR-139139, hsa-miR-182, hsa-miR-182*, hsa-miR- 183,hsa-miR-183*, hsa-miR-188-3p, hsa-miR-1973, hsa-miR-200b, hsa-miR-3621,hsa-miR-378a, hsa- miR-429, hsa-miR-582, hsa-miR-96, hsa-miR-99b*hsa-miR-133a-1, hsa-miR-133b, hsa-miR-139139, hsa-miR-182, hsa-miR-182*,hsa-miR-183, hsa-miR- 183*, hsa-miR-188-3p, hsa-miR-200b, hsa-miR-210,hsa-miR-378a, hsa-miR-429, hsa-miR-449a, hsa- miR-96, hsa-miR-99b*hsa-miR-133a-1, hsa-miR-133b, hsa-miR-139139, hsa-miR-182, hsa-miR-182*,hsa-miR-183, hsa-miR- 183*, hsa-miR-188-3p, hsa-miR-200b, hsa-miR-378a,hsa-miR-429, miR-96, hsa-miR-99b* hsa-miR-1291, hsa-miR-1973,hsa-miR-210, hsa-miR-3621, hsa-miR-449a, hsa-miR-582, hsa-miR-99b*hsa-miR-3621, hsa-miR-665, hsa-miR-1291, hsa-miR-1973, hsa-miR-33b*,hsa-miR-3607-5p, hsa-miR- 1181, hsa-miR-1469, hsa-miR-602, hsa-miR-205,hsa-miR-183, hsa-miR-182*, hsa-miR-182, hsa-miR-3621, hsa-miR-665,hsa-miR-1291, hsa-miR-1973, hsa-miR-33b*, hsa-miR-3607-5p, hsa-miR-1181, hsa-miR-1469, hsa-miR-602 hsa-miR-3621, hsa-miR-153, hsa-miR-33b*,hsa-miR-1973, hsa-miR-183*, hsa-miR-96, hsa-miR-375, hsa-miR-182,hsa-miR-183 hsa-miR-3621, hsa-miR-153, hsa-miR-33b*, hsa-miR-1973,hsa-miR-183*, hsa-miR-665, hsa-miR-582, hsa-miR-182, hsa-miR-378a,hsa-miR-96, hsa-miR-200b, hsa-miR-191, hsa- miR-429, hsa-miR-494,hsa-miR-99b*, hsa-miR-375, hsa-miR-141, hsa-miR-183*, hsa-miR-148*, hsa-miR-1291, hsa-miR-185, hsa-miR-1973, hsa-miR-103, hsa-miR-133a-1,hsa-miR-3607-5p, hsa-miR- 133b, hsa-miR-1-1, hsa-miR-210 hsa-miR-3621,hsa-miR-1291, hsa-miR-1973, hsa-miR-449a hsa-miR-99b*, hsa-miR-133b,hsa-miR-183*, hsa-miR-188-3p, hsa-miR-139139, hsa-miR-429, hsa-miR-378a, hsa-miR-200b, hsa-miR-182*, hsa-miR-96, hsa-miR-133a-1,hsa-miR-183, hsa-miR-449a, hsa-miR-210 hsa-miR-99b*, hsa-miR-133b,hsa-miR-183*, hsa-miR-188-3p, hsa-miR-139, hsa-miR-429, hsa-miR- 378a,hsa-miR-200b, hsa-miR-182*, hsa-miR-96, hsa-miR-133a-1, hsa-miR-183hsa-miR-133b, hsa-miR-182, hsa-miR-183 hsa-miR-582, hsa-miR-99b*,hsa-miR-449a, hsa-miR-210 hsa-miR-3621, hsa-miR-1291, hsa-miR-1973,hsa-miR-449a hsa-miR-3621, hsa-miR-665, hsa-miR-1291, hsa-miR-1973hsa-miR-3621, hsa-miR-665 hsa-miR-3621, hsa-miR-33b*, hsa-miR-1973,hsa-miR-375, hsa-miR-182, hsa-miR-183, hsa-miR-602, hsa-miR-1291,hsa-miR-103, hsa-miR-148*, hsa-miR-182*, hsa-miR-185, hsa-miR-191,hsa-miR-210, hsa-miR-494, hsa-miR-582, hsa-miR-3621, hsa-miR-183,hsa-miR-375, hsa-miR-665, hsa-miR-96, hsa-miR-663, hsa-miR-182, hsa-miR-494, hsa-miR-148a*, hsa-miR-1291, hsa-miR-602, hsa-miR-182*,hsa-miR-33b*, hsa-miR-1973, hsa-miR-153-1/hsa-miR-153-2, hsa-miR-141*,hsa-miR-1469, hsa-miR-1181 and hsa-miR-3607-5p hsa-miR-3621,hsa-miR-665, hsa-miR-1291, hsa-miR-1973, hsa-miR-33b*, hsa-miR-3607-5p,hsa-miR- 1181, hsa-miR-1469 and hsa-miR-602. hsa-miR-205 and hsa-miR-221hsa-miR-153, hsa-miR-182, hsa-miR-183, hsa-miR-183*, hsa-miR-375 andhsa-miR-96 hsa-miR-153, hsa-miR-183* hsa-miR-3621, hsa-miR-33b* andhsa-miR-1973 hsa-miR-183*, hsa-miR-185, hsa-miR-133a-1, hsa-miR-1-1hsa-miR-665, hsa-miR-582, hsa-miR-182, hsa-miR-378a, hsa-miR-96,hsa-miR-200b, hsa-miR-191, hsa- miR-429, hsa-miR-494, hsa-miR-99b*,hsa-miR-375, hsa-miR-141, hsa-miR-148*, hsa-miR-1291, hsa- miR-1973,hsa-miR-103, hsa-miR-3607-5p, hsa-miR-133b and hsa-miR-210 hsa-miR-665,hsa-miR-3621, hsa-miR-1973, hsa-miR-1291, hsa-miR-192 and hsa-miR-183hsa-miR-665, hsa-miR-3621, hsa-miR-1973, hsa-miR-1291 and hsa-miR-192.hsa-miR-96, hsa-miR-182*, hsa-miR-449a, hsa-miR-210, hsa-miR-429,hsa-miR-188, hsa-miR-200b, hsa-miR-183 and hsa-miR-183* hsa-miR-183*,hsa-miR-188-3p, hsa-miR-429, hsa-miR-200b, hsa-miR-182*, hsa-miR-96 andhsa-miR- 183 hsa-miR-133a-1/hsa-miR-133a-2, hsa-miR-133b, hsa-miR-378aa,hsa-miR-99b*, hsa-miR-1-1/hsa- miR-1-2, hsa-miR-139, hsa-miR-92b andhsa-miR-582 hsa-miR-99b*, hsa-miR-133b, hsa-miR-139, hsa-miR-378a andhsa-miR-133a-1. hsa-miR-182 and hsa-miR-183 hsa-miR-133b hsa-miR-582,hsa-miR-99b*, hsa-miR-449a and hsa-miR-210 hsa-miR-1291, hsa-miR-1973and hsa-miR-449a hsa-miR-3621 hsa-miR-1-1/hsa-miR-1-2, hsa-miR-96,hsa-miR-141, hsa-miR-153-1/hsa-miR-153-2, hsa-miR-182, hsa-miR-183,hsa-miR-375, hsa-miR-494, hsa-miR-582, hsa-miR-1291, hsa-miR-1973,hsa-miR-3621, hsa-miR-133a-1/hsa-miR-133a-2, hsa-miR-133b, hsa-miR-182*,hsa-miR-183*, hsa-miR-33b*, hsa- miR-99b*

TABLE 25 Diagnostic (PC vs BPH) Prognostic (G8 vs G6) Log Log miRNA nameFC P-value miRNA name FC P-value hsa-miR-665 −1.38 1.68E−04 hsa-miR-5821.83 4.41E−02 hsa-miR-582 −6.56 4.44E−10 hsa-miR-99b* 2.07 8.15E−02hsa-miR-182 −2.57 4.44E−06 hsa-miR-449a 2.69 5.14E−03 hsa-miR-378 −1.136.35E−06 hsa-miR-210 0.92 1.92E−02 hsa-miR-96 −4.02 2.16E−05hsa-miR-200b −1.96 6.17E−05 hsa-miR-191 −1.67 1.00E−04 hsa-miR-429 −2.841.87E−04 hsa-miR-494 −1.86 2.33E−04 hsa-miR-99b* −2.83 1.40E−03hsa-miR-375 −1.49 2.40E−03 hsa-miR-141 −1.43 3.56E−03 hsa-miR-183* 0.876.03E−03 hsa-miR-148* −2.52 7.87E−03 hsa-miR-1291 −2.01 7.95E−03hsa-miR-185 0.84 1.07E−02 hsa-miR-1973 −1.51 1.30E−02 hsa-miR-103 −1.181.38E−02 hsa-miR-133a-1 1.23 1.47E−02 hsa-miR-3607-5p −0.67 1.91E−02hsa-miR-133b −1.59 1.92E−02 hsa-miR-1-1 1.65 2.31E−02 hsa-miR-210 −0.606.53E−02

TABLE 26 Diagnostic Prognostic (G8 vs (PC vs ctrl) G6) G6 vs Ctrl G8 vsCtrl miRNA miRNA miRNA miRNA Log name Log FC name Log FC name Log FCname FC hsa-miR-665 −2.05 hsa-miR- −0.65 hsa-miR- −1.63 hsa-miR- −2.273621 3621 3621 hsa-miR- −1.74 hsa-miR- 0.84 hsa-miR-665 −2.16 hsa-miR-−2.04 3621 1291 665 hsa-miR- −1.15 hsa-miR- 0.68 hsa-miR- −1.57 19731973 1291 hsa-miR- −1.06 hsa-miR- 1.01 hsa-miR- −1.15 1291 449a 1973hsa-miR-192 −0.67 hsa-miR-183 −0.84

TABLE 27 First data set Second data set sens- spec- auc- sens- spec-size names auc-med med med S + S med med med S + S 2 mir1-1 + mir58292.61 91.67 90.91 1.83 87.57 76.00 92.86 1.69 2 mir183* + mir582 94.8995.83 90.91 1.87 87.00 72.00 92.86 1.65 2 mir185 + mir582 92.42 100.0086.36 1.86 88.14 88.00 82.14 1.70 2 mir210 + mir582 88.45 95.83 86.361.82 87.14 80.00 85.71 1.66 3 mir1- 94.51 100.00 86.36 1.86 89.29 80.0089.29 1.69 1 + mir183* + mir582 3 mir1- 92.80 100.00 86.36 1.86 87.7188.00 82.14 1.70 1 + mir185 + mir582 3 mir1- 92.80 91.67 90.91 1.8387.29 80.00 85.71 1.66 1 + mir1973 + mir582 3 mir1- 92.61 91.67 90.911.83 87.71 76.00 89.29 1.65 1 + mir221 + mir582 3 mir1- 92.23 100.0086.36 1.86 86.57 88.00 82.14 1.70 1 + mir33b* + mir582 3 mir1- 97.16100.00 90.91 1.91 85.43 100.00 53.57 1.54 1 + mir582 + mir96 3 mir133a-95.27 95.83 90.91 1.87 85.43 72.00 89.29 1.61 1 + mir183* + mir582 3mir133b + mir183* + 94.89 95.83 90.91 1.87 86.43 72.00 89.29 1.61 mir5823 mir183* + mir185 + 94.13 100.00 86.36 1.86 89.29 72.00 96.43 1.68mir582 3 mir183* + mir221 + 94.32 100.00 86.36 1.86 87.57 72.00 96.431.68 mir582 3 mir183* + mir33b* + 94.32 95.83 90.91 1.87 87.57 92.0075.00 1.67 mir582 3 mir183* + mir375 + 95.83 95.83 90.91 1.87 85.4384.00 82.14 1.66 mir582 3 mir183* + mir582 + 94.70 95.83 90.91 1.8787.29 72.00 96.43 1.68 mir665 3 mir185 + mir210 + 97.73 91.67 95.45 1.8786.29 92.00 71.43 1.63 mir582 3 mir185 + mir221 + 94.51 100.00 86.361.86 86.86 92.00 75.00 1.67 mir582 3 mir185 + mir33b* + 92.61 100.0086.36 1.86 88.43 88.00 82.14 1.70 mir582 3 mir185 + mir375 + 95.45100.00 86.36 1.86 85.57 84.00 78.57 1.63 mir582 3 mir185 + mir378 +97.54 100.00 90.91 1.91 86.86 92.00 71.43 1.63 mir582 3 mir185 +mir582 + 93.56 100.00 86.36 1.86 89.29 88.00 78.57 1.67 mir665 3mir185 + mir582 + 96.59 100.00 90.91 1.91 87.29 72.00 92.86 1.65 mir96 3mir210 + mir582 + 95.27 100.00 90.91 1.91 85.57 72.00 85.71 1.58 mir96

1. A method for analysing a subject sample, comprising a step ofdetermining the level of at least one biomarker selected from:hsa-miR-3621 (SEQ ID NO:1) and the other 34 biomarkers in Table 17 inthe sample, wherein the level of the biomarker provides a diagnosticindicator of whether the subject has prostate cancer and/or a prognosticindicator of whether the subject has prostate cancer in the aggressiveform or indolent form.
 2. The method of claim 1, wherein the levels ofat least two Table 17 biomarkers (a ‘panel’) are measured in the sample.3. The method of claim 2, wherein the panel comprises marker(s) fromTable
 1. 4. The method of claim 2, wherein the panel comprises marker(s)from Table
 2. 5. The method of claim 2, wherein the panel includes (i)any one of the 34 biomarkers in Table 17 in combination with (ii) any ofthe other 33 biomarkers in Table
 17. 6. The method of claim 2, whereinthe panel is a panel from Tables 3 to 9 herein.
 7. The method of claim2, wherein the panel is a panel from Tables 10 to 16 herein.
 8. Themethod of claim 1, wherein up to 7 biomarkers from Table 17 aremeasured.
 9. The method of claim 1, including measurement of at leastone of: (a) a known biomarker for PC, which may or may not be miRNA;and/or (b) other information about the subject; and/or (c) otherdiagnostic tests or clinical indicators for PC.
 10. A method fordiagnosing a subject as having PC, comprising steps of: (i) determiningthe levels of at least 2 biomarkers of Table 17 in a sample from thesubject; and (ii) comparing the determination from step (i) to dataobtained from samples from subjects without PC and/or from subjects withPC, wherein the comparison provides a diagnostic indicator of whetherthe subject has PC.
 11. A method for monitoring development of PC in asubject, comprising steps of: (i) determining the levels of at least 1biomarker of Table 17 in a first sample from the subject taken at afirst time; and (ii) determining the levels of that biomarker of Table17 in a second sample from the subject taken at a second time, wherein:(a) the second time is later than the first time; and (b) a change inthe level(s) of the biomarker(s) in the second sample compared with thefirst sample indicates that PC is in remission or is progressing.
 12. Adevice for the diagnosis and/or prognosis of PC, wherein the devicepermits determination of the level(s) of at least 1 Table 17 biomarker.13. A kit comprising reagents for measuring the levels of at least 2different Table 17 biomarkers.
 14. The use of a Table 1 biomarker as adiagnostic biomarker for prostate cancer.
 15. The use of a Table 2biomarker as a prognostic biomarker for prostate cancer.